Diagnostic, predictive and prognostic testing for cancer

ABSTRACT

The present invention relates generally to the field of cancer. In particular, the present invention relates to cancer prognostic and treatment protocols.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 13/873,487, filed Apr. 30, 2013, now abandoned, which is acontinuation of U.S. patent application Ser. No. 12/738,062, filed Jul.26, 2010, now U.S. Pat. No. 8,512,716, which is the National stage ofInternational Application Number PCT/GB2008/003501, filed Oct. 15, 2008,which is hereby incorporated by reference herein in its entirety,including any figures, tables, nucleic acid sequences, amino acidsequences, and drawings.

FIELD OF INVENTION

The present invention relates generally to the field of cancer. Inparticular, the present invention relates to cancer prognostic andtreatment protocols.

BACKGROUND

The majority of cells in the human body reside in non-proliferating,out-of-cycle states and only a minority population is actively cycling.These cycling cells are mainly located in stem-transit amplifyingcompartments of self-renewing tissues such as cervix, colon or skin. Incontrast, most functional cells (e.g. hepatocyctes) reside in aquiescent (G0), reversibly arrested state, or have irreversiblywithdrawn from the mitotic cell division cycle into terminallydifferentiated states (e.g. neurons, myocytes, or surface colonicepithelial cells). Cancers, on the contrary, are characterized byuncontrolled cell growth and therefore contain a high proportion ofcycling cells.

Cells are responsive to mitogens in their environment at a discrete timein G1, referred to as the restriction point. The absence of mitogensdoes not affect cell cycle progression through S, G2 and M phase untilcells return to their sensitive window in G1. In response to high celldensity or mitogen deprivation, cells accumulate with a 2N DNA contentand exit into G0. The cell cycle phase transitions are driven by changesin cyclin-CDK pairs. Cyclin D-CDK4, cyclin D-CDK6 and cyclin E-CDK2regulate G0/G1 and are required for full E2F activity, S phase isinitiated by cyclinA-CDK2, and cyclin B-CDK1 regulates progressionthrough G2 and entry into mitosis. What distinguishes cells inout-of-cycle states from cells engaged in cycle remains to beelucidated.

Cancer is a complex group of heterogeneous diseases caused by theaccumulation of gene mutations, which increase the activity ofregulatory genes that stimulate cell proliferation and decrease theactivity of proteins that normally restrain it. Activation of dominantstimulatory oncogenes or inactivation of recessive tumour suppressorgenes, through point mutation, gene amplification, hypermethylation,translocation, or interaction with viral oncoproteins, can affect alllevels of growth signalling pathways including mitogens, mitogen growthfactor receptors, Ras, Raf, ABL, PI3 kinase AKt upstream to moleculessuch as pi 61NK4A, Myc, cyclin D, cyclin E, pRB and p53 downstream.

Microarray gene expression profiling is ideally suited for analysis ofthe complex multifactorial, interactive and stepwise alterations in geneexpression that characterise tumourigenesis and is currently anintensive area of investigation aimed at identifying unique molecularsignatures that can be exploited for cancer diagnosis and prognosis.Interestingly, the expression arrays include a proliferation signature,genes whose expression pattern correlates with tumour grade(differentiation status), cell cycle status and doubling times. Thisproliferation signature is one of the most prominent gene-expressionpatterns observed in tumour datasets, regardless of the tissue fromwhich it is derived and includes many cell cycle regulated genes such asE2F1, BUB1, PLK1, cyclins E1, D1 and B1.

Unfortunately, the actual performance of prediction rules using geneexpression has not turned out to be as informative as initiallysuggested for many tumour types and the list of genes identified can behighly unstable. For example, most predictive rules using geneexpression have not provided a significantly improved prognosticclassification for breast cancer when compared to conventionalclinicopathological criteria such as tumour differentiation status,extent of spread and proliferation index. Indeed, many of the publishedgene signatures predicting distant-metastasis free survival in cancershave been found to correlate significantly with differentiation status.

The global microarray approach for identification of clinically usefulproliferation signatures is potentially constrained. Firstly, themicroarray approach in some part assumes a single compartment tumourmodel, in which cancers are composed of proliferating, exponentiallygrowing cells. Neoplasms, however, are highly heterogeneous with regardto the cell cycle state of individual tumour cells. For example, inwell-differentiated, low-grade tumours only a very small fraction ofclonogenic tumour cells may be cycling, but in which the majority haveexecuted their differentiation programmes and irreversibly withdrawnfrom cycle into a differentiated state (sterile compartment). Thusbenign hyperproliferative conditions (e.g. hyperplasia) andphysiological reparative growth, reactive pathological conditionscontaining large numbers of mitotic cells, may give higher proliferationsignatures than well-differentiated cancers.

Secondly, tumour cells in vivo might also withdraw reversibly from cycleinto a non-proliferating G0 state. Indeed, in many tumours thenon-proliferating cells are the majority; that is the growth fraction(the ratio of proliferating to total cells) is less than 0.5. Thissituation is perhaps not surprising, because normal tissues are composedof mixed proliferating and non-proliferating elements and some remnantof this complex behaviour is hardwired into most cancers. The presenceof contaminating benign neoplastic cells, tumour stroma, lymphoidfollicles, intra- and peri-tumoural inflammatory infiltrates, and otherconnective tissues such as blood vessels also distorts the analysis byadding large numbers of cells with additional complex cell cyclekinetics. Hence the complex and heterogeneous cell cycle kinetics withinindividual tumours are likely to hinder identification of clinicallyuseful microarray proliferation signatures, a problem that has alsoconstrained the use of flow cytometry in routine clinical practice.

The use of flow cytometry has also had a limited impact since clinicalsamples are often not suitable for such analysis. This is partly due tofixation artifacts, inadequate amounts of tissue, and because ofinterpretation difficulties due to contaminating populations fromreactive stroma and/or benign elements.

Assessment of cell proliferation markers has not previously provided anyprognostic and predictive solution, and experts in the field have beensceptical that proliferation markers will provide useful clinicalinformation. There is a belief that measuring parameters of cellproliferation will provide objective information about tumours, butdespite numerous studies there is little direct evidence that the use ofcertain cell proliferation markers are really an improvement onconventional histological assessment optimally employed. Few studieshave even addressed the critical issue of the relative value ofproliferation markers compared to the standard histopathological gradingand staging.

While gene expression has been applied to predicting the outcome incancers, the actual performance of prediction rules using geneexpression has not turned out to be as informative as initiallysuggested. For example, currently most predictive rules using geneexpression have not provided a significantly improved prognosticclassification when compared to the conventional NPI prognostic factorsin breast cancer. The identification of new biomarkers to improveprognostic assessment in common cancers is therefore urgently required.

Breast cancer is an example of a common cancer and is a complex diseasedue to its morphological and biological heterogeneity, its tendency toacquire chemo-resistance and the existence of several molecularmechanisms underlying its pathogenesis. Half of women who receiveloco-regional treatment for breast cancer will never relapse, whereasthe other half will eventually die from metastatic disease. It istherefore imperative to distinguish clearly between these two groups ofpatients for optimal clinical management. Unfortunately, prognosticmarkers for breast cancers are at present limited. There is also lack ofa test (predictive test) which allows selection of the most appropriateanti-cancer drugs particularly in the context of the new generation ofsmall molecule inhibitors that target critical kinases involved ingrowth control and cell cycle transitions. For example in breast cancerpredictive testing is presently limited to Her2 immunoexpressionprofiling.

Epithelial ovarian carcinoma (EOC) is another common cancer and is thefourth most common cancer in women in the U.S. and the U.K. Patientsoften presents with advanced disease, and despite improvements in drugtherapy, survival is poor. At present, tumour stage is the mostimportant prognostic factor. Residual disease after surgery, histologicsubtype, and tumour grade also predict survival, but give littleinformation about the biological variables responsible for stageprogression and outcome.

Their remains a need for improved diagnostic, prognostic and predictiveapproaches to diseases caused by abnormal proliferation, such ascancerous or pre-cancerous conditions.

The present invention is directed to alleviating at least onedisadvantage associated with the prior art.

Any discussion of documents, devices, acts or knowledge in thisspecification is included to explain the context of the invention. Itshould not be taken as an admission that any of the material forms apart of the prior art base or the common general knowledge in therelevant art on or before the priority date of the disclosure and claimsherein.

SUMMARY OF INVENTION

Further scope of applicability of the present invention will becomeapparent from the detailed description given hereinafter. However, itshould be understood that the detailed description and specificexamples, while indicating preferred embodiments of the invention, aregiven by way of illustration only, since various changes andmodifications within the spirit and scope of the invention will becomeapparent to those skilled in the art from this detailed description.

In a first aspect, the present invention provides a method ofdetermining the presence or absence of abnormally proliferating cells orcellular growth abnormality in a body sample from an individual, themethod including detecting in the sample a biomarker, wherein thebiomarker is selected from group consisting of DNA replication licensingfactors, Aurora kinases, Ki67, geminin, Polo-like kinases, and theirsubstrate Histone H3 (referred to as “H3S10ph” hereinafter) andcombinations thereof.

In one embodiment, the biomarker is detected using a specific bindingmember directed against a target polypeptide of the biomarker.

In a second aspect, the present invention provides a method ofcategorising a tissue as (i) normal or (ii) potentially or actuallypre-cancerous or cancerous, dysplastic or neoplastic, the methodincluding determining binding to a sample of the tissue of a specificbinding member directed against a biomarker, wherein the biomarker isselected from group consisting of DNA replication licensing factors,Aurora kinases, Ki67, geminin, Polo-like kinases, H3S10ph andcombinations thereof.

In one embodiment, the specific binding member is directed against atarget polypeptide of the biomarker.

In one embodiment, the pattern or degree of binding may be compared withthat for a known normal sample and/or a known abnormal sample.

In one embodiment, the ratio of one biomarker versus a further biomarkeris determined.

In a third aspect, the present invention provides a method of markingabnormal cells within a tissue sample, the method including contactingthe sample with a specific binding member directed against a targetpolypeptide, wherein the target polypeptide is selected from groupconsisting of DNA replication licensing factors, Aurora kinases, Ki67,geminin, Polo-like kinases, H3S10ph, and combinations thereof, underconditions wherein the specific binding member binds to abnormallyproliferating cells and not normal cells.

In a fourth aspect, the present invention provides the use of a specificbinding member directed against a target polypeptide, for determining,assessing or diagnosing the presence or absence of abnormal cellularproliferation, cellular growth abnormality, tumour cell cycle kinetics,cell cycle phase distribution, dysplasia, neoplasia, or a potentially oractually pre-cancerous or cancerous state in a tissue or sample thereof.

In one embodiment, the target polypeptide comprises two or more markersselected from the group comprising DNA replication licensing factors,Aurora kinases, Ki67, geminin, Polo-like kinases, H3S10ph andcombinations thereof.

In a fifth aspect, the present invention provides a method of predictingresponse to therapy or predicting disease progression in a cancer, themethod comprising determining the presence or absence of abnormallyproliferating cells or cellular growth abnormality in a body sample froman individual, the method including detecting in the sample a targetpolypeptide, wherein the target polypeptide is selected from groupconsisting of DNA replication licensing factors, Aurora kinases, Ki67,geminin, Polo-like kinases, H3S10ph and combinations thereof.

In a sixth aspect, the present invention provides a method of monitoringresponse to therapy drug development studies, the method comprisingdetecting in a body sample a biomarker, wherein the biomarker isselected from group consisting of DNA replication licensing factors,Aurora kinases, Ki67, geminin, Polo-like kinases, and H3S10ph andcombinations thereof, assessing the biomarker expression to determinethe presence or absence of abnormal cellular proliferation, cellulargrowth abnormality, tumour cell cycle kinetics, cell cycle phasedistribution, dysplasia, neoplasia, or a potentially or actuallypre-cancerous or cancerous state in the sample.

In one embodiment, the drug development studies are preclinical drugdevelopment studies.

In one embodiment, the drug development studies are preclinical drugdevelopment studies.

In some embodiments, the preclinical drug development studies are invivo xenograft tumour models.

In a seventh aspect, the present invention provides a method fordetermining a prognosis of progression of a cancer in a subject, themethod comprising the steps of:

(a) assessing a level of a first biomarker selected from at least one ofMcm2-7 in a biological sample from the subject; and

(b) assessing the level of a second biomarker selected from at least oneof geminin, Aurora A, Plk1, Ki67 and H3S10ph in the biological samplefrom the subject,

-   -   wherein the combination of the level of the first biomarker        compared to a pre-determined value and the level of the second        biomarker compared to a pre-determined value is indicative of        cancer progression in the subject.

In one embodiment, the method of determining the progression of cancerin the subject further comprises assessing the level of a thirdbiomarker selected from at least one of geminin, Aurora A, Plk1, Ki67and H3S10ph in the biological sample from the subject, wherein thesecond and third biomarkers are different.

In an eighth aspect, the present invention provides a method fordetermining a treatment protocol for a subject having cancer, the methodcomprising the steps of:

(a) assessing a level of a first biomarker selected from at least one ofMcm2-7 in the biological sample from the subject; and

(b) assessing the level of a second biomarker selected from at least oneof geminin, Aurora A, Plk1, Ki67 and H3S10ph in the biological samplefrom the subject,

wherein the combination of the level of the first biomarker compared toa pre-determined value and the level of the second biomarker compared toa pre-determined value is indicative of the treatment regimen prescribedfor the subject.

In one embodiment, the method of determining a treatment protocol for asubject having cancer further comprises assessing the level of a thirdbiomarker selected from at least one of geminin, Aurora A, Plk1, Ki67and H3S10ph in the biological sample from the subject, wherein thesecond and third biomarkers are different.

In a ninth aspect, the present invention provides a method fordetermining efficacy of a therapeutic treatment of a subject havingcancer, the method comprising the steps of:

(a) assessing the level of a first biomarker selected from at least oneof Mcm2-7 in the biological sample from the subject; and

(b) assessing the level of a second biomarker selected from at least oneof geminin, Aurora A, Plk1, Ki67 and H3S10ph in the biological samplethe subject,

wherein the combination of the level of the first biomarker compared toa pre-determined value and the level of the second biomarker compared toa pre-determined value is indicative of the efficacy of the therapeutictreatment.

BRIEF DESCRIPTION OF THE DRAWINGS

Further disclosure, objects, advantages and aspects of the presentinvention may be better understood by those skilled in the relevant artby reference to the following description of preferred embodiments takenin conjunction with the accompanying drawings, which are given by way ofillustration only, and thus are not limiting to the scope of the presentinvention, and in which:

FIG. 1 shows the presence of Ki67, Mcm2, geminin, Aurora A and H3S10phduring the mitotic cell division cycle. Levels of the Mcm2-7 DNAreplication licensing factors do not vary significantly during passagethrough the cell cycle, whereas expression of the endogenous licensingrepressor protein geminin is restricted to S-G2-M phase. Increasedgeminin expression has been noted in several malignancies and correlatespositively with proliferation. Notably, this increased expression isalways restricted to S-G2-M, even in aggressive tumours. Aurora A (andPLK1; data not shown) levels are negligible during G1, and increaseduring S phase to reach a peak during G2/M. Presence of H3S10ph isrestricted to mitosis and thus can be used as a mitotic marker. Mcm 2-7protein expression can be used to determine cell cycle state in tissues.Mcm2-7 identify cells engaged in cell cycle (G1-S-G2-M phases) but aretightly down-regulated following withdrawal into quiescent (G0),differentiated, and senescent “out of cycle” states. Since Ki67 isexpressed throughout the cell cycle in proliferating cells, the ratio ofan S-G2-M phase or M phase marker with Ki67 (e.g. geminin/Ki67, AuroraA/Ki67 or H3S10ph/Ki67) can be used as an indicator of the relativelength of G1 phase and therefore the rate of cell cycle progression.

FIG. 2 shows a schematic diagram of DNA replication licensing factorexpression in self-renewing tissues. The model includes stem cell,dividing-transit, and functional compartments. The flux of cells throughthese compartments is continuous; new cells are supplied from the stemcell compartment (S) and their number is amplified in thedividing-transit compartment (T). Cells become fully differentiated andfunctionally competent as they enter the mature compartment (M). Thestem cell compartment shows low expression of the DNA replicationlicensing factors Mcm2-7. Mcm2-7 levels rapidly increase as cells enterthe dividing-transit compartment. There is a gradual down-regulation ofMcm2-7 as cells differentiate and adopt a fully differentiatedfunctional phenotype. However, proliferative capacity is lost at anearlier point during execution of the differentiation programme as cellexit the division-transit compartment and is coupled to down-regulationof the Mcm2-7 loading factor Cdc6. Notably, the arrested differentiationthat characterizes cancer, particularly in high-grade tumours, isassociated with a failure to down-regulate Mcm2-7.

FIGS. 3A and 3B show cell cycle phase progression in breast cancer. Twobreast cancer biopsy specimens immunostained for Mcm2, Ki67, geminin,Aurora A and H3pare shown in FIGS. 3A and 3B. Both cases arecharacterised by high Mcm2 protein expression, indicating that themajority of tumour cells are engaged in the cell division cycle.Although both tumour specimen show a high growth fraction as defined byMcm2 expression, there are striking differences in expression of theS-G2-M markers geminin and Aurora A and the mitotic marker H3S10ph.(FIG. 3A) This tumour shows very low expression levels of geminin andAurora A and a small number of cells show phosphorylation of Histone H3at serine 10 (H3S10ph), indicating an arrested or prolonged G1 phase.(FIG. 3B) In contrast, this tumour shows high expression levels ofgeminin and Aurora A and increased H3S10 phosphorylation, indicatingrapid cell cycle phase progression. Thus it can be postulated that thetumour shown in FIG. 3B is more responsive to S or G2/M cell cycle phasespecific drugs.

FIG. 4 shows multiparameter analysis of DNA replication licensingfactors, Aurora kinases, Ki67, geminin, Polo-like kinases, H3S10ph andcombinations thereof for prognostic and predictive cancer testing. Usingthese combination of markers in a multiparameter analysis it is possibleto determine whether tumour cells have withdrawn from cycle (i.e.sterile tumour cells), a population which will be resistant to cellcycle directed anti-cancer agents and radiation. Moreover for thosetumour cells engaged in cycle (Mcm 2-7-positive) it is possible todetermine the rate of cell cycle progression.

FIGS. 5A and 5B show a validation of the biomarker multi-parameteranalysis. (FIG. 5A) Immunoblots of asynchronous MCF-7 total cell lysateswith antibodies to Mcm2, geminin, Aurora A, Plk1 and H3S10ph. (FIG. 5B)Photomicrographs of paraffin-embedded tissue sections of Grade 3 breastcancer immunohistochemically stained with antibodies to Ki67, Mcm2,geminin, Aurora A, Plk1 and H3S10ph (Original magnification 400×). Insetshows immunostaining of normal breast (Magnification 800×).

FIGS. 6A and 6B show Aurora A and Plk1 expression across tumour gradesfor breast cancer series.

FIGS. 7A-7C show time to recurrence curves by (FIG. 7A) NPI, (FIG. 7B)Plk1, and (FIG. 7C) Aurora A for breast cancer series.

FIG. 8 shows the hazard ratios of cell cycle biomarkers.

FIGS. 9A and 9B show time to recurrence curves by (FIG. 9A) NPI and Plk1and (FIG. 9B) NPI and Aurora A for breast cancer series.

FIGS. 10A-10C. (FIG. 10A) Immunoblots of asynchronous HeLa S3 total celllysates with antibodies against Mcm2, geminin, Aurora A, Aurora B andH3S10ph. (FIG. 10B) Immunoblots of biomarkers and actin (loadingcontrol) in total cell lysates from synchronized HeLa S3 cells. FACSprofiles of synchronized HeLa S3 cells at 2-hour intervals. (FIG. 10C)Photomicrographs of paraffin-embedded tissue sections of epithelialovarian carcinoma (EOC) immunohistochemically stained with antibodiesagainst Ki67, Mcm2, geminin, Aurora A, Aurora B and H3S10ph. Originalmagnification, 400×; inset, 1000×.

FIG. 11 shows Aurora A expression across tumour grades (EOC series).

FIGS. 12A-12F show Kaplan-Meier curves showing association betweenAurora A, tumour ploidy status, and patient survival for EOC series.(FIG. 12A) Aurora A (lower tertile<11.3%, middle tertile 11.3-21.3%,upper tertile >21.3%) and disease-free survival across whole series; logrank test, p=0.01. (FIG. 12B) Tumour ploidy status and disease-freesurvival across whole series; log rank test, p=0.03. (FIG. 12C) Aurora A(lower tertile<8.7%, middle tertile 8.7-19.6%, upper tertile>19.6%) anddisease-free survival in early stage subgroup; log rank test, p=0.004.(FIG. 12D) Tumour ploidy status and disease-free survival in early stagesubgroup; log rank test, p=0.04. (FIG. 12E) Aurora A (lowertertile<8.7%, middle tertile 8.7-19.6%, upper tertile>19.6%) and overallsurvival in early stage subgroup; log rank test, p=0.01. (FIG. 12F)Tumour ploidy status and overall survival in early stage subgroup; logrank test, p=0.08.

FIG. 13 is a graphical representation showing distribution of Mcm2expression in the study sample. Frequency of Mcm2 protein expressionacross the breast cancer patient cohort. (Mean=64.4101, Std.Dev.=30.4632, N=182).

FIG. 14 is a graphical representation showing distribution of cell cyclebiomarker expression defines three distinct cell cycle phenotypes; (I)out-of-cycle state; (II) in cycle G1 delayed/arrested state; (III)actively cycling state. The median (solid black line), interquartilerange (boxed), and robust range excluding outlying cases (enclosedlines) are shown. Outlying cases are shown by isolated points. (LI:labeling index).

FIG. 15 is a graphical representation of Kaplan-Meier curves showingassociation between cell cycle phenotype and disease-free survival. (I)out-of-cycle state; (II) in cycle G1 delayed/arrested state; (III)actively cycling state. On univariate analysis comparing phenotype IIIwith phenotypes I and II combined; HR=3.90 (1.81-8.40), p<0.001. Onmultivariate analysis adjusted for PI, HR=2.71 (1.18-6.23), p=0.19.

FIG. 16 is a graphical representation showing relationship between cellcycle phenotype and breast cancer subtypes. The panels shows theproportion of each breast cancer subtype which display cell cyclephenotypes I (out of cycle), II (GI delayed/arrested) and III (activelycycling). Notably, the majority of Her-2 and triple negative tumoursdisplay the actively cycling phenotype (III).

DETAILED DESCRIPTION

The utility of biomarkers, including clinical utility, and how analysisof these biomarkers can be integrated with other key cell cycleregulators to provide information on cell cycle kinetics and phasedistribution in patient tumour samples is provided. This analysis mayprovide diagnostic algorithms for improving prognostic assessment andalso has potential to predict therapeutic response to cell cycle phasespecific drugs. This is an approach in which a multiparameter cell cycleanalysis may be performed on routine patient tumour biopsy materialusing biomarkers that form core constituents of the DNA replicationlicensing pathway and mitotic machinery. This algorithm provides notonly a prognostic tool but can also be exploited as a predictive testfor cell cycle phase specific drugs (including radiation) or drugsinhibiting upstream growth regulatory pathways. The algorithm can alsobe exploited to assess the efficacy of novel drug candidates inpreclinical (in vivo xenograft tumour models) studies and clinicaltrials.

In a first aspect, the present invention provides a method ofdetermining the presence or absence of abnormally proliferating cells orcellular growth abnormality in a body sample from an individual, themethod including detecting in the sample a biomarker, wherein thebiomarker is selected from group consisting of DNA replication licensingfactors, Aurora kinases, Ki67, geminin, Polo-like kinases, and theirsubstrate Histone H3 (referred to as “H3S10ph” hereinafter) andcombinations thereof.

In one embodiment, the biomarker is detected using a specific bindingmember directed against a target polypeptide of the biomarker.

By “body sample” is intended any sampling of cells, tissues, or bodilyfluids in which expression of a biomarker can be detected. Examples ofsuch body samples include but are not limited to blood, lymph, urine,gynecological fluids, biopsies, and smears. Body samples may be obtainedfrom a patient by a variety of techniques including, for example, byscraping or swabbing an area or by using a needle to aspirate bodilyfluids. Methods for collecting various body samples are well known inthe art. Body samples may be transferred to a glass slide for viewingunder magnification. Fixative and staining solutions may be applied tothe cells on the glass slide for preserving the specimen and forfacilitating examination.

In one embodiment, the body sample is derived from any one of cervix,including testing cervical smears, the breast, urinary tractmalignancies (tested on both biopsy tissue samples and on urine cytologysmears), colon, lung, bladder, skin, larynx, oesophagus, bronchus, lymphnodes, and haematological malignancies, also blood and serum forevidence of metastatic sarcoma and carcinoma. In some embodiments, thepresent invention may additionally be employed in assessment ofpre-malignant abnormalities of cervical glandular epithelial cells(glandular intra-epithelial neoplasia, GIN) or pre-malignantabnormalities in other tissues.

In some embodiments, it may be particularly appropriate for employmentin cytological or biochemical assessment of other clinical specimenswhere detection of neoplastic cells, or their distinction from cellsshowing reactive changes, can be very difficult. Such specimens includesputum, bronchio-alveolar lavage specimens, urine and brushings from thealimentary tract (including oesophagus, stomach and pancreas, both bileduct and pancreatic duct).

In some embodiments, the present invention may be applied inhistological or biological assessment of tissue where assessment ofproliferation may enable more accurate prediction of clinical outcome,and/or more rational selection of therapy. Specimens may includemalignancies of glandular cells (eg. lung, breast, colon, prostate,stomach), squamous cells (eg. lung, skin, oesophagus) or otherepithelial cell types (eg. bladder, ureter, kidney, ovary).

In one embodiment, multiparameter analysis of Mcm2, Mcm3, Mcm4, Mcm5,Mcm6, Mcm7, geminin, Aurora A and Aurora B, and their substrate histoneH3 may be used to evaluate the progression of EOC and the cell cyclekinetics of this tumour type, either in vitro or in vivo.

In a second aspect, the present invention provides a method ofcategorising a tissue as (i) normal or (ii) potentially or actuallypre-cancerous or cancerous, dysplastic or neoplastic, the methodincluding determining binding to a sample of the tissue of a specificbinding member directed against a biomarker, wherein the biomarker isselected from group consisting of DNA replication licensing factors,

Aurora kinases, Ki67, geminin, Polo-like kinases, H3S10ph andcombinations thereof.

In one embodiment, the specific binding member is directed against atarget polypeptide of the biomarker.

In one embodiment, the pattern or degree of binding may be compared withthat for a known normal sample and/or a known abnormal sample.

In one embodiment, the ratio of one biomarker versus a further biomarkeris determined.

A “biomarker” is any gene or protein whose level of expression in abiological sample is altered compared to that of a pre-determined level.The pre-determined level can be a level found in a biological samplefrom a normal or healthy subject. Biomarkers of the invention areselective for abnormally proliferating cells or cellular growthabnormality.

In another embodiment of the present invention, the biomarker is anygene or protein whose level is altered compared to a pre-determinedlevel of expression in a biological sample. For example, thepre-determined value for a first biomarker in the biological sample isgreater than 20%, greater than 25%, or 30% or greater of cells positivein the biological sample for the first biomarker.

In a related aspect, the pre-determined value for a second or thirdbiomarker in the biological sample is less than 20%, less than 15%, lessthan 10% or 7% or less of cells positive in the biological sample forthe second or third biomarker.

The biomarkers of the invention include genes and proteins, and variantsand fragments thereof. Such biomarkers include DNA comprising the entireor partial sequence of the nucleic acid sequence encoding the biomarker,or the complement of such a sequence. The biomarker nucleic acids alsoinclude RNA comprising the entire or partial sequence of any of thenucleic acid sequences of interest. A biomarker protein is a proteinencoded by or corresponding to a DNA biomarker of the invention. Abiomarker protein comprises the entire or partial amino acid sequence ofany of the biomarker proteins or polypeptides.

The present invention is based on the surprising discovery thattargeting biomarkers of the DNA replication licensing pathway (eg Mcm2,Mcm3, Mcm4, Mcm5, Mcm6, Mcm7 and geminin) which regulates G1-S phasetransition combined with biomarkers of the mitotic machinery (eg AuroraA and its substrate H3) which are involved in the G2-M transition, byimmunoexpression profiling in routinely fixed surgical biopsy material,provides a unique insight into the cell cycle kinetics of these tumours.Using these combination of markers in a multiparameter analysis it ispossible to determine whether tumour cells have withdrawn from cycle(i.e. sterile tumour cells), a population which will be resistant tocell cycle directed anti-cancer agents and radiation. Moreover for thosetumour cells engaged in cycle (Mcm 2-7-positive) it is possible todetermine the rate of cell cycle progression.

Tumours showing delayed progression and residing mainly in G1 are likelyto show a poor response to S and G2-M phase directed agents (Table 1)and therefore should be treated with G1 directed agents (tumourphenotype—Mcm2-7 levels high but associated with low geminin, Aurora Aand H3S10ph levels and geminin/Ki67 ratios tending towards zero). Incontrast tumours showing accelerated cell cycle progression are likelyto show a good response to S and G2/M directed agents (Table 1) (tumourphenotype—Mcm2-7 levels high, geminin high, Aurora A high, H3S10ph highwith geminin/Ki67 ratios tending towards 1). Tumours showing acceleratedcell cycle progression and a high G2-M fraction are also likely to showthe best response to radiation. Especially useful are binding moleculesdirected against core constituents of the DNA replication licensingpathway (Mcm2-7 family of proteins and geminin) and binding moleculesdirected against core constituents of the mitotic machinery (Aurora A,Polo-like kinase1 and H3S10ph). Other biomarkers may be utilized as afurther parameter in the algorithm that allows analysis of the rate ofcell cycle progression. Biomarkers that allow analysis of the rate ofcell cycle progression include Ki67.

In one embodiment, the present invention provides a method ofdetermining the cell cycle kinetics of tumour populations in routinelyprocessed surgical biopsy material. The multiparameter algorithm allowsnon-proliferating out-of-cycle (sterile) cells that are refractory tocell cycle phase specific drugs and radiation to be distinguished fromactively cycling cells. The multiparameter analysis allows the precisetumour cell cycle kinetics to be determined and thus allows theselection of cell cycle phase directed drugs most appropriate to treatthat particular patient (personalised medicine) (Table 1). In additionto acting a potentially powerful predictive test for guiding therapeuticinterventions, this multiparameter analysis provides a powerfulprognostic tool for determining time to relapse (disease freesurvival/disease free interval) and time to death (overall survival).

In a third aspect, the present invention provides a method of markingabnormal cells within a tissue sample, the method including contactingthe sample with a specific binding member directed against a targetpolypeptide, wherein the target polypeptide is selected from groupconsisting of DNA replication licensing factors, Aurora kinases, Ki67,geminin, Polo-like kinases, H3S10ph, and combinations thereof, underconditions wherein the specific binding member binds to abnormallyproliferating cells and not normal cells.

Whether or not the specific binding member binds to the sample may bedetermined in order to ascertain the presence of abnormallyproliferating cells within the sample.

In a fourth aspect, the present invention provides the use of a specificbinding member directed against a target polypeptide, for determining,assessing or diagnosing the presence or absence of abnormal cellularproliferation, cellular growth abnormality, tumour cell cycle kinetics,cell cycle phase distribution, dysplasia, neoplasia, or a potentially oractually pre-cancerous or cancerous state in a tissue or sample thereof.

In one embodiment, the target polypeptide comprises two or more markersselected from the group comprising DNA replication licensing factors,Aurora kinases, Ki67, geminin, Polo-like kinases, H3S10ph andcombinations thereof.

Precise duplication of DNA during each cell division cycle is essentialfor genomic stability and is achieved through tightly regulatedinitiation events. DNA replication initiation depends on the assembly ofprereplicative complexes at replication origins during late mitosis andearly G₁ phase. Prereplicative complex assembly involves sequentialbinding of origin recognition complex (ORC), Cdc6, Cdt1, and Mcm2-7 toorigins and renders chromatin “licensed” for DNA synthesis during Sphase. Regulation of DNA replication licensing factors such as Mcm2-7protein levels, provides a powerful downstream mechanism for controllingcell proliferation in human tissues. Mcm2-7 dysregulation is an earlyevent in multistep tumourigenesis. Inhibition of prereplicative complexreassembly, which ensures that origins are fired once-and-only-once percell cycle, is critical for maintaining genomic integrity.

The licensing repressor geminin is expressed at high levels duringS-G2-M phases and blocks Mcm2-7 reloading onto chromatin through itsinteraction with Cdt1. In human cell populations in vivo, depletion ofgeminin results in profound genomic instability with overreplication ofDNA, resulting in the emergence of cells with giant aneuploid nuclei,which are the morphologic/pathologic hallmarks of aggressive cancers.Inactivation of geminin also causes centrosome overduplication, which,together with abrogated G2-M checkpoint mechanisms, results in multiplemitotic defects that may promote chromosome missegregation andaneuploidy. These findings emphasize the key role that geminin plays inmaintaining genomic integrity at multiple stages of the cell cycle.

Rigorous control of mitotic events is essential for successfulcompletion of sister-chromatid segregation and cell division. AlthoughCDKs are the master regulators of mitotic entry, they do not act alone.Polo-like kinase 1 (PLK1), Aurora A and Aurora B are three additionalprotein kinases that control a subset of critical mitotic events.Transit through mitosis is dependent on protein kinases such aspolo-like kinase (PLK) and the Aurora kinases. The Aurora kinases areimportant regulators of several stages of mitosis, including centrosomematuration and separation, chromosome orientation and segregation, andcytokinesis.

Like geminin, endogenous levels of the Aurora kinases are tightlyregulated in a cell cycle-dependent manner, with low levels at G1-S,accumulation during G2-M, and rapid degradation at the end of mitosis.

Tumour cell cycle kinetics not only impacts on prognostic algorithms,but is also of importance for predicting response to cell cycle phasespecific drugs (see above). Applicants have demonstrated that analysisof core constituents of the cell cycle machinery using simpleimmunohistological techniques, and applied directly to routine surgicalbiopsy material, provides a detailed and unique insight into the tumourcell cycle kinetic profile that is operating in vivo.

As discussed above, Mcm2, Mcm3, Mcm4, Mcm5, Mcm6 and Mcm7 (referred toherein as “Mcm2-7” or “Mcm2 to 7”) expression allows cells traversingthrough the cycle to be distinguished from those residing in“out-of-cycle” states. The origin licensing inhibitor geminin is onlydetectable during S-G2-M phases, as are the mitotic kinases PLK1, AuroraA and B. Histone H3 is a substrate for the Aurora kinases and isphosphorylated only in mitosis. Phosphohistone H3 (H3S10ph) is thus amarker of M phase. Multi-parameter analysis of these G1/S and G2/Mregulators therefore provides a detailed characterization of the cellcycle state in surgical biopsy material (routinely fixed and processed).For example, in resting premenopausal breast, Mcm2-7 expression is highbut geminin, Aurora A/B, PLK1 and H3S10ph protein levels are low,indicating that mammary luminal epithelium resides in a G1 extended orarrested state, a phenotype also observed in premalignant lesions andslow growing neoplasms. In contrast, in rapidly growing aggressivetumours, not only are expression levels of Mcm2-7 high, but there isincreasing expression of S-G2-M and M phase markers. This profile isindicative of accelerated cell cycle progression which appears tocorrelate with increasing tumour grade (less differentiated state),increasing genomic instability and reduced survival.

Cell cycle biomarker analysis is therefore of value as a predictor oftherapeutic response, particularly for cell cycle phase specific drugs.For example, the expression levels of Aurora A and PLK1, potent targetsfor small molecule inhibitors, vary widely in ovarian and breast cancer.These tumours also display very different cell cycle kinetics and cellcycle phase distributions. Tumours showing accelerated cell cycleprogression and high expression levels of these target proteins are mostlikely to show the greatest response to such mechanism based therapeuticinterventions.

Analysis of cell cycle kinetics may also be used to monitor the responseto drugs which impact on cell cycle progression through activation ofcheckpoint pathways in abnormally proliferating cells or cellular growthabnormality. For example, immunoexpression analysis of geminin, AuroraA, PLK1, H3S10ph and gemini/Ki67 in pre- and post-treatment biopsymaterial may provide a readout to identify tolerable doses of UCN-01that can then be used to abrogate cisplatin-induced cell cycle arrest.

In some embodiments, immunocytochemistry techniques are provided thatutilize antibodies to detect the overexpression of biomarkerpolypeptides in a sample from an individual. In this aspect of theinvention, at least one antibody directed to a specific biomarker ofinterest is used. Overexpression can also be detected by nucleicacid-based techniques, including, for example, hybridization and RT-PCR.Kits comprising reagents for practicing the methods of the invention arefurther provided.

Although the methods of the invention require the detection of at leastone biomarker in a patient sample for the detection of disease, in someembodiments 2, 3, 4, 5, 6, 7, 8, 9, 10 or more biomarkers may be used topractice the present invention. It is recognized that detection of morethan one biomarker in a body sample may be used to identify instances ofdisease. Therefore, in some embodiments, two or more biomarkers areused, more preferably, two or more complementary biomarkers. By“complementary” is intended that detection of the combination ofbiomarkers in a body sample results in the successful identification ofdisease in a greater percentage of cases than would be identified ifonly one of the biomarkers was used. Thus, in some cases, a moreaccurate determination of disease can be made by using at least twobiomarkers.

Accordingly, where at least two biomarkers are used, at least twoantibodies directed to distinct biomarker polypeptides will be used topractice the immunocytochemistry methods disclosed herein. Theantibodies may be contacted with the body sample simultaneously orconcurrently.

In one embodiment, the method according to any one of the first to fifthaspect may comprise detecting in the sample a further targetpolypeptide, wherein the target polypeptide is selected from groupconsisting of cell cycle regulated genes that are specific to the G1/Sphase boundary or to S-phase. Such genes include but are not limited tohelicase (DDX11), uracil DNA glycolase (UNG), E2F5, cyclin E1 (CCNE1),cyclin E2 (CCNE2), CDC25A, CDC45L, CDC6, p21 WAF-1(CDKN1A), CDKN3, E2F1,NPAT, PCNA, stem loop BP (SLBP), BRCA1, BRCA2, CCNG2, CDKN2C,dihydrofolate reductase (DHFR), histone H1, histone H2A, histone H2B,histone H3, histone H4, MSH2, NASP, ribonucleotide reductase M1 (RRM1),ribonucleotide reductase M2 (RRM2), thymidine synthetase (TYMS),replication factor C4 (RFC4), RAD51, chromatin Factor 1A (CHAF1A),chromatin Factor 1B (CHAF1B), topisomerase III (TOP3A), ORC1, primase 2A(PRIM2A), CDC27, primase 1 (PRIM1), flap structure endonuclease (FEN1),fanconi anemia comp. grp A (FNACA), PKMYT1, and replication protein A2(RPA2). Other S phase genes of interest include cyclin-dependent kinase2 (CDK2), DNA polymerase I alpha (DNA POLI), DNA ligase 1, B-Myb, DNAmethyl transferase (DNA MET), pericentrin (PER), KIF4, DP-1, ID-3, RANbinding protein (RANBP1), gap junction alpha 6 (GJA6), amino levulinatedehydratase (ALDH), histone 2A Z (H2A.Z), spermine synthase (SpmS),proliferin 2, T-lymphocyte activation protein, phospholipase A2 (PLA2),and L6 antigen (L6).

In some embodiments, the biomarkers comprise genes that are induced bythe E2F transcription factor. Such genes include but are not limited tothymidylate synthase, thymidine kinase 1, ribonucleotide reductase M1,ribonucleotide reductase M2, CDK2, cyclin E, PCNA, DNA primase smallsubunit, topoisomerase II A (Topo2A), DNA ligase 1, flap endonuclease 1,RAD51, CDC2, cyclin A2, cyclin B1, cyclin B2, KIFC1, FIN16, BUB1,importin alpha-2, HMG2, enhancer of zeste, STK-1, histone stem-loop BP,Rb, P18-INK4C, annexin VIII, c-Myb, CDC25A, cyclin D3, cyclin E1,deoxycytosine kinase, DP-1, endothelin converting enzyme, enolase 2, P18INK4C, ribonucleotide reductase, and uracil DNA glycolase 2. Inparticular embodiments the biomarker of interest is a gene induced byE2F transcription factor that is involved in cell cycle regulation andDNA replication, such as, for example, cyclin E2, p57KIP2, RANBPM, andreplication protein A1. Some E2f-induced genes of interest are involvedin apoptosis, including APAF1, Bcl-2, caspase 3, MAP3 Kinase 5, and TNFreceptor associated factor. Other E2f-induced genes are involved in theregulation of transcription and include, for example, ash2 like,polyhomeotic 2, embryonic ectoderm protein, enhancer of zeste,hairy/enhancer of split, homeobox A10, homeobox A7, homeobox A9,homeodomain TF1, pre-B-cell leukemia FT3, YY1 TF, POU domain TF,TAFII130, TBP-factor 172, basic TF3, bromodomain/zinc finger, SWI/SNF,ID4, TEA-4, NFATC1, NFATC3, BT, CNC-1, MAF, MAFF, MAFG, core bindingprotein, E74-like factor 4, c-FOS, JUNB, zinc finger DNA BP, andCbp/p300 transactivator. E2F-induced genes involved in signaltransduction are also potential biomarkers of interest and include TGFbeta, follistatin, bone morphogenetic protein 2, BMP receptor type 1A,frizzled homolog 1, WNT10B, sphingosine kinase 1, dual specificityphosphatase 7, dual specificity (Y) phosphatase, FGF Receptor 3, proteintyrosine phosphatase, dual specificity (Y) phosphatase D6655, insulinreceptor, mature T-cell proliferation 1, FGF receptor 2, TGF alpha,CDC42 effector protein 3, Met, CD58, CD83, TACC1, and TEAD4.

If a tissue is categorised as potentially or actually pre-cancerous orcancerous, on the basis of detected abnormality in a tissue sample inaccordance with the present invention, appropriate diagnostic and/orclinical follow-up will be called for.

The present invention also provides predictive methods for determiningthe course of therapy for the diagnosed condition.

Accordingly, in a fifth aspect, the present invention provides a methodof predicting response to therapy or predicting disease progression in acancer, the method comprising determining the presence or absence ofabnormally proliferating cells or cellular growth abnormality in a bodysample from an individual, the method including detecting in the samplea target polypeptide, wherein the target polypeptide is selected fromgroup consisting of DNA replication licensing factors, Aurora kinases,Ki67, geminin, Polo-like kinases, H3S10ph and combinations thereof.

Cellular growth abnormalities include pre-cancerous or cancerous cells,other disorders of cellular proliferation including, but not limited to,psoriasis and inflammatory bowel disease such as ulcerative colitis andCrohn's disease.

In addition to being cellular proliferation disorders in their ownright, inflammatory bowel diseases may be a precursor to a cancerousstate, although not in all patients, so their detection by means of thepresent invention may be used to provide valuable results for closerfollow-up. In inflammatory bowel disease there may be sloughing of cellsof the colon and bowel, allowing for analysis to be performed on faecalsamples and preparations of cells from such samples.

Samples to be subjected to a contact with a specific binding member inaccordance with various aspects of the present invention may be preparedusing any available technique which allows binding of a specific bindingmolecule to the target polypeptide, determination of nucleic acidlevels, enzymatic activity and so on, in accordance with differentembodiments of the present invention. Various techniques are standard inthe art, e.g. (for molecules such as antibodies binding targetpolypeptide) as used in fixing cells for immunohistochemistry.

The detection of a specific binding member such as an antibody oncontrol and test samples may be determined by any appropriate means.Tagging with individual reporter molecules is one possibility. Thereporter molecules may directly or indirectly generate detectable, andpreferably measurable, signals. The linkage of reporter molecules may bedirectly or indirectly, covalently, e.g. via a peptide bond ornon-covalently. Linkage via a peptide bond may be as a result ofrecombinant expression of a gene fusion encoding binding molecule (e.g.antibody) and reporter molecule.

One favoured mode is by covalent linkage of each binding member with anindividual fluorochrome, phosphor or laser dye with spectrally isolatedabsorption or emission characteristics. Suitable fluorochromes includefluorescein, rhodamine, phycoerythrin and Texas Red. Suitablechromogenic dyes include diaminobenzidine.

Other reporters include macromolecular colloidal particles orparticulate material such as latex beads that are coloured, magnetic orparamagnetic, and biologically or chemically active agents that candirectly or indirectly cause detectable signals to be visually observed,electronically detected or otherwise recorded. These molecules may beenzymes which catalyse reactions that develop or change colours or causechanges in electrical properties, for example. They may be molecularlyexcitable, such that electronic transitions between energy states resultin characteristic spectral absorptions or emissions. They may includechemical entities used in conjunction with biosensors. Biotin/avidin orbiotin/streptavidin and alkaline phosphatase detection systems may beemployed. Further examples are horseradish peroxidase andchemiluminescence.

A specific binding molecule may be provided in a kit, which may includeinstructions for use in accordance with the present invention. Such kitsare provided as a further aspect of the present invention. One or moreother reagents may be included, for example labelling molecules.Reagents may be provided within containers which protect them from theexternal environment, such as a sealed vial. A kit may include one ormore articles for providing the test sample itself depending on thetissue of interest, e. g. a swab for removing cells from the buccalcavity, a syringe for removing a blood sample, a spatula for taking acervical smear, a biopsy gun and so on (such components generally beingsterile).

A kit may include any combination of or all of a blocking agent todecrease non-specific staining, a storage buffer for preserving bindingmolecule activity during storage, staining buffer and/or washing bufferto be used during antibody staining, a positive control, a negativecontrol and so on. Positive and negative controls may be used tovalidate the activity and correct usage of reagents employed inaccordance with the invention and which may be provided in a kit.Controls may include samples, such as tissue sections, cells fixed oncoverslips and so on, known to be either positive or negative for thepresence of the target, such as one or more of the biomarkers describedherein. The design and use of controls is standard and well within theroutine capabilities of those of ordinary skill in the art.

Samples may be removed from the body using any convenient means andtechnique. A spatula or swab may be used to remove endothelium cells, e.g. from the cervix or buccal cavity. Blood and other fluid samples maybe removed using a syringe or needle. Other tissue samples may beremoved by biopsy or tissue section.

In a sixth aspect, the present invention provides a method of monitoringresponse to therapy drug development studies, the method comprisingdetecting in a body sample a biomarker, wherein the biomarker isselected from group consisting of DNA replication licensing factors,Aurora kinases, Ki67, geminin, Polo-like kinases, and H3S10ph andcombinations thereof, assessing the biomarker expression to determinethe presence or absence of abnormal cellular proliferation, cellulargrowth abnormality, tumour cell cycle kinetics, cell cycle phasedistribution, dysplasia, neoplasia, or a potentially or actuallypre-cancerous or cancerous state in the sample.

In one embodiment, the drug development studies are preclinical drugdevelopment studies.

In one embodiment, the drug development studies are preclinical drugdevelopment studies.

In some embodiments, the preclinical drug development studies are invivo xenograft tumour models.

A seventh aspect of the present invention provides a method fordetermining a prognosis of progression of a cancer in a subject, themethod comprising the steps of:

-   -   (a) assessing a level of a first biomarker selected from at        least one of Mcm2-7 in a biological sample from the subject; and    -   (b) assessing the level of a second biomarker selected from at        least one of geminin, Aurora A, Plk1, Ki67 and H3S10ph in the        biological sample from the subject,    -   wherein the combination of the level of the first biomarker        compared to a pre-determined value and the level of the second        biomarker compared to a pre-determined value is indicative of        cancer progression in the subject.

In a related embodiment, the method of determining the prognosis ofprogression of a cancer further comprises assessing the level of a thirdbiomarker selected from at least one of geminin, Aurora A, Plk1, Ki67and H3S10ph in the biological sample from the subject, wherein thesecond and third biomarkers are different.

In a further embodiment, when the level of the first biomarker comparedto a pre-determined value is low and the level of the second biomarkercompared to a pre-determined value is low, the subject's prognosis isindicative of a reduced likelihood of cancer progression.

In a related embodiment, when the level of the first biomarker comparedto a pre-determined value is low and the level of the second biomarkercompared to a pre-determined value is low, the subject's prognosis isindicative of a 5 year survival rate of greater than 80%, 85% or 89%.

In another embodiment, when the level of the first biomarker compared toa pre-determined value is high and the level of the second biomarkercompared to a pre-determined value is low, the subject's prognosis isindicative of a reduced likelihood of cancer progression.

In a related embodiment, when the level of the first biomarker comparedto a pre-determined value is high and the level of the second biomarkercompared to a pre-determined value is low, the subject's prognosis isindicative of a 5 year survival rate of greater than 80%, 85% or 87%.

In a further embodiment, when the level of the first biomarker comparedto a pre-determined value is high and the level of the second biomarkercompared to a pre-determined value is high, the subject's prognosis isindicative of an increased likelihood of cancer progression.

In a related embodiment, when the level of the first biomarker comparedto a pre-determined value is high and the level of the second biomarkercompared to a pre-determined value is high, the subject's prognosis isindicative of a 5 year survival rate of less than 70%, 60% or 56%.

The levels of the biomarkers of the present invention can be measuredusing any means known to the skilled artisan. In one aspect, the levelsof biomarkers can be measured using an immunological assay method, suchas, but not limited to, dot blots, slot blots, RIA, microarray andELISA. In another aspect, the levels of the biomarkers can be measuredusing a molecular biological-based assay method, such as, without beinglimited to, Northern blot analysis, Southern blot analysis, Western blotanalysis, RT-PCR, PCR, nucleic acid sequence based amplification assays(NASBA), transcription mediated amplification (TMA), or computerizeddetection matrix.

It is important to note that the order in which the levels of the first,second, third or subsequent biomarkers are measured is not important.For example, all biomarkers may be measured concurrently. Alternatively,the second or third or subsequent biomarker may be assessed prior to thelevel of the first biomarker.

In an eighth aspect, the present invention provides a method fordetermining a treatment protocol for a subject having cancer, the methodcomprising the steps of:

(a) assessing a level of a first biomarker selected from at least one ofMcm2 to 7 in the biological sample from the subject; and

-   -   (b) assessing the level of a second biomarker selected from at        least one of geminin, Aurora A, Plk1, Ki67 and H3S10ph in the        biological sample from the subject,    -   wherein the combination of the level of the first biomarker        compared to a pre-determined value and the level of the second        biomarker compared to a pre-determined value is indicative of        the treatment regimen prescribed for the subject.

In a related aspect, the method of determining a treatment protocol fora subject further comprises assessing the level of a third biomarkerselected from at least one of geminin, Aurora A, Plk1, Ki67 and H3S10phin the biological sample from said subject, wherein the second and thirdbiomarkers are different.

In a further embodiment, when the level of the first biomarker comparedto a pre-determined value is low and the level of the second biomarkercompared to a pre-determined value is low, the treatment regimen isselected from one or more of:

(a) monitoring; and

(b) treatment with non-cell-cycle specific chemotherapeutic agents.

In another embodiment, when the level of the first biomarker compared toa pre-determined value is high and the level of the second biomarkercompared to a pre-determined value is low, the treatment regimen isselected from one or more of:

(a) monitoring;

(b) treatment with G1 or non-cell cycle specific agents; and

(c) treatment with non-S and G2/M cell cycle specific chemotherapeuticagents.

In yet a further embodiment, when the level of the first biomarkercompared to a pre-determined value is high and the level of the secondbiomarker compared to a pre-determined value is high, the treatmentregimen is selected from one or more of:

(a) surgery; and

(b) treatment with S and G2/M cell cycle specific chemotherapeuticagents.

Non-cell cycle chemotherapeutic agents include, without being limitedto, mitomycin C (MMC),1-(4-amino-2-methylpyrimidine-5-yl)-methyl-3-(2-chloroethyl)3-nitrosourea hydro-chloride (ACNU), and nitrogen mustard (HN2), cis-platinum,4-hydroperoxy-cyclo-phosphamide, Flavopiridol.

S-phase ell cycle agents include, without being limited to,5-fluorouracil, hydroxyurea, methotrexate, epirubicin, etoposide,methotrexate, 5-fluororacil, 5-fluorodeoxyuridine, cytarabine,gemcitabine, cladribine, thioguanine, fludarabine, Hydroxyurea,topoisomerase I inhibitors (irinotecan, topotecan), Topoisomerase IIinhibitors (etoposide, teniposide, anathracyclines, epirubicin).

G1 cell cycle agents include, without being limited to, asparaginase,prednisolone.

G2/M cell cycle agents include, without being limited to, etoposide,cisplatin, staurosporine, ZM447439, Vinca alkaloids, (vindesine,vinelobrine, vincristine, vinblastine), Taxanes (paclitaxel, docetaxel),Bleomycin, staurosporine, ZM447439 (Aurora kinase A and B inhibitor),B12536 (Polo-like kinase I inhibitor).

M cell cycle agents include, without being limited to, docetaxel, BI2536.

Agents which work at multiple steps within a cell cycle include, withoutbeing limited to, Flavopiridol.

While this invention has been described in connection with specificembodiments thereof, it will be understood that it is capable of furthermodification(s). This application is intended to cover any variations,uses or adaptations of the invention following in general, theprinciples of the invention and comprising such departures from thepresent disclosure as come within known or customary practice within theart to which the invention pertains and as may be applied to theessential features hereinbefore set forth.

As the present invention may be embodied in several forms withoutdeparting from the spirit of the essential characteristics of theinvention, it should be understood that the above described embodimentsare not to limit the present invention unless otherwise specified, butrather should be construed broadly within the spirit and scope of thepresent invention as defined in the appended claims. Variousmodifications and equivalent arrangements are intended to be includedwithin the spirit and scope of the present invention and appendedclaims.

“Comprises/comprising” when used in this specification is taken tospecify the presence of stated features, integers, steps or componentsbut does not preclude the presence or addition of one or more otherfeatures, integers, steps, components or groups thereof.”

EXAMPLES Example 1 DNA Replication Licensing Factors and Mitotic KinasesDefine Proliferative State and Are Linked to Clinical Outcome in BreastCancer Study Cohort

-   -   182 patients diagnosed with invasive breast cancer were        identified from the breast cancer database held in the        department of Surgery, UCL Hospitals, London, UK. All patients        studied underwent regular postoperative clinical assessment and        contributed to the cross-sectional analyses. 10 were lost to        follow-up and 5 had recurrent cancer, of whom 2 died from breast        cancer. 167 patients contributed to the prospective analyses of        survival and relapse, of whom 24 (14%) died from cancer within        the study period, 12 died from other unrelated causes, and 131        were still alive at last follow-up. There were 40 (24%) relapse        events comprising relapses and deaths from cancer. The median        follow-up period was 47 months (range: 1-92 months). The mean        time to relapse amongst those who relapsed was 26 months        (standard deviation (SD)=15 months, range: 2-55 months). The        mean follow-up time amongst those who had not yet relapsed was        52 months (SD=20 months, range: 2-92 months). The mean survival        time amongst those who had died was 21 months (SD=12 months,        range: 4-44 months). The mean follow-up time amongst those who        had not yet died was 50 months (SD=21 months, range: 1-92        months). Formalin-fixed, paraffin-embedded surgical breast        tissue from these patients was retrieved from the pathology        archives which included all three histological grades (1-3) as        determined by the Nottingham modification of the Bloom and        Richardson method. Histological reports and slides were        available for all cases. These included 142 invasive ductal        carcinomas, 26 lobular, four mucinous, one micropapillary and        nine of mixed type. Parameters recorded included histological        grade, tumour size, tumour type, lymph node status,        lymphovascular invasion (LVI), age and NPI. We also studied        randomly selected cases of normal breast tissue from 21        premenopausal women who had undergone reduction mammoplasty.        Local research ethics committee approval for the study was        obtained from the joint UCL/UCLH Committees on the Ethics of        Human Research.

Antibodies

Rabbit polyclonal antibody against human geminin was generated asdescribed (Wharton SB, Hibberd S, Eward K L, et al. Br J Cancer 2004;91:262-9). Ki67 MAb (clone MIB-1) was obtained from DAKO (Glostrup,Denmark), Mcm2 MAb (clone 46) from BD Transduction Laboratories(Lexington, Ky.), oestrogen receptor-α (ER) MAb (clone 1D5) andprogesterone receptor MAb (clone PgR 636) from DAKO, Aurora A MAbNCL-L-AK2 (clone JLM28) from Novocastra Laboratories (Newcastle, UK),Polo-like kinase 1 (PLK1) MAb (clone 35-206) and Histone H3phosphorylated on Serine 10 (H3S10ph) PAb from Upstate (Lake Placid,N.Y.).

Cell Culture

Human MCF-7 breast epithelial adenocarcinoma cells (ATCC HTB-22) werecultured in EMEM (Gibco-BRL, Invitrogen, Carlsbad, Calif., USA)supplemented with 2 mM Glutamine, 1% Non-Essential Amino Acids, 10% FCS,100 U/ml penicillin and 0.1 mg/ml streptomycin.

Preparation of Protein Extracts and Immunoblotting

MCF7 cells were harvested by treatment with trypsin, washed in PBS, andresuspended in lysis buffer (50 mM Tris-CI pH 7.5, 150 mM NaCl, 20 mMEDTA, 0.5% NP40) at 2×10⁷ cells/ml. After incubation on ice for 30 min,the lysate was clarified by centrifugation (13,000 g, 15 min, 4° C.).Lysates were separated by 4-20% SDS-PAGE [75 pg protein/well] andimmunoblotted as described (Stoeber et al. J Cell Sci, 114:2027-41,2001). Blocking, antibody incubations, and washing steps were performedusing the following conditions: PBS/0.1% A Tween-20/5% milk for Mcm2,Aurora A and PLK1, PBS/1% Tween-20/10% milk for geminin, and PBS/5% milkfor H3S10ph.

Immunohistochemistry

Archival formalin-fixed, paraffin-embedded tissue (PWET) obtained atinitial diagnosis was available for all patients and for each specimen ablock was chosen that contained a representative sample of invasivetumour. 3 μm sections were cut onto Superfrost Plus slides (VisionsBiosystems, UK), dewaxed in xylene, and rehydrated through gradedalcohol to water. Tissue sections were pressure cooked in 0.1 M citratebuffer at pH 6.0 for 2 min and immunostained using the Bond™ PolymerRefine Detection kit and Bond™-Max automated system (Vision Biosystems,Newcastle Upon Tyne, UK). Primary antibodies were applied at thefollowing dilutions: Ki67 (1/300), Mcm2 (1/2000), geminin (1/600), ER(1/200), PR (1/200), Aurora A (1/70), PLK1 (1/1000) and H3S10ph (1/300).HER-2 immunostaining was performed using the DAKO HercepTest™ (DAKO),according to the manufacturer's instructions. Coverslips were appliedwith Pertex mounting medium (Cell Path Ltd, Newtown Powys, UK).Incubation without primary antibody was used as negative control andcolonic epithelial sections as positive controls.

Protein Expression Profile Analysis

Protein expression analysis was performed by determining the labellingindex (LI) of the markers in each tumour as described (Shetty et al. BrJ Cancer 93:1295-300, 2005, Dudderidge et al. Clin Cancer Res 11:2510-7,2005). Slides were evaluated at low power magnification (100×) toidentify regions of tumour with the highest intensity of staining. Fromthese selected areas, three to five fields at 400× magnification werecaptured with a charged coupled device camera and analysis software(SIS, MOnster, Germany). Images were subsequently printed forquantitative analysis, which was undertaken with the observer unaware ofthe clinico-pathological variables. Both positive and negative cellswithin the field were counted and any stromal or inflammatory cells wereexcluded. Criteria for identification of positive cells were dependenton the biomarker: for Ki67, Mcm2, geminin, ER, PR and H3S10ph, cellswith any degree of nuclear staining were scored positive; for Aurora Aand PLK1, cells with any degree of nuclear or cytoplasmic staining werescored positive (Gritsko et al. Clin Cancer Res 9:1420-6, 2003). Aminimum of 500 cells were counted for each case. The LI was calculatedusing the following formula: LI=number of positive cells/total number ofcells×100. For evaluation of HER-2 protein over-expression, membranestaining was assessed following the FDA approved scoring systemrecommended by DAKO.

DNA Image Cytometry

For each case, one 40 μm section of PWET obtained from the same block asthat assessed by IHC was used to prepare nuclei as described (Sudbo etal. N Engl J Med 344:1270-8, 2001. Haroske et al. Anal Cell Pathol 1998;17:189-200, 1997). The Fairfield DNA Ploidy System (Fairfield ImagingLtd, Nottingham, UK) was used for image processing, analysis andclassification as described (Sudbo et al. 2001 supra.). Lymphocytes andplasma cells were included as internal controls and 40 μm sections ofhigh-grade bladder tumour and normal colonic tissue as external controlsfor aneuploid and diploid populations, respectively. Histograms wereclassified according to published criteria (Sudbo et al. 2001 supra,Haroske 1998 supra). Histograms were classified by two independentassessors with a high level of agreement without knowledge ofclinico-pathological variables. For statistical analysis, tetraploid andpolyploid tumours were grouped together with aneuploid tumours.

Statistical Analysis

Biomarkers were summarised with the median and interquartile range. TheMann-Whitney U-test was used to compare each marker with Lymph nodestage, ploidy status, and with grade 3 against the normal sample. TheJonckheere-Terpstra non-parametric test for trend was used to comparemarkers with grade and Her2 status. Spearman's rank correlationcoefficient was used to assess associations between markers and NPI. Thechi-squared test for linear by linear association with one degree offreedom was used to test for association between Her2 and ploidy status.The unpaired t-test was used to compare mean NPI according to ploidystatus.

Linear regression was used to assess for trend in mean NPI across Her2.Cox regression was used in the analysis of cancer recurrence and cancerdeath to provide hazard ratios and to assess the prediction of markers,split into two categories at the median, both in univariate models andin multivariate models adjusting for NPI. Kaplan-Meier plots were usedto show the estimated predictive effects of markers ignoring, and alsostratified by, NPI category. All analyses involved two-sided tests, witheffects summarised using 95% confidence intervals and assessed asstatistically significant at the 5% level using SPSS software (version12.0.1).

Results Validation of Biomarker Multi-Parameter Analysis and ItsBiological Implications

Monospecificity of antibodies against Mcm2, geminin, Aurora A, PLK1 andH3S10ph was confirmed in total cell extracts from asynchronous MCF7cells by detection of a single protein with a molecular mass consistentwith the reported electrophoretic mobility of the corresponding humanantigen (FIG. 5A). In a separate study of this biomarker set in HeLa S3cells and SK-OV 3 ovarian cancer cells we have demonstrated that Mcm2levels do not vary significantly during passage through the cell cycle,whereas geminin expression is restricted to S-G2-M. Aurora A and PLK1levels are negligible during G1, increase during S phase and reach apeak during G2/M, with degradation occurring 2-4 hours after releasefrom mitotic arrest. Presence of H3S10ph is restricted to mitosis,consolidating the rational for its use as a mitotic marker. Since theproliferation marker Ki67 is present throughout the cell cycle inproliferating cells, the ratio of an S-G2-M phase or M phase marker withKi67 (e.g. geminin/Ki67, Aurora A/Ki67 or H3S10ph/Ki67) can be used asan indicator of the relative length of G1 phase and therefore the rateof cell cycle progression. Notably, increased geminin expression isrestricted to S-G2-M, even in aggressive tumours.

Protein expression analysis of these cell cycle markers was firststudied in normal breast specimens following reduction mammoplasty(n=21). High level Mcm2 expression was observed in epithelial cells ofthe terminal duct lobular unit (TDLU), indicating that these cellsreside in an “in-cycle” state (median: 33.5%). Whereas the level of Mcm2expression was high, Ki67 was expressed at low levels (median: 2.8%).Notably, geminin, Aurora A, PLK1 (S-G2-M phase makers) and H3S10ph (Mphase marker) are only expressed in a very small fraction of cells (<1%)of the TDLU, indicating a block to cell cycle progression. Takentogether, this cell cycle phenotype is consistent with a G1 arrestedstate. By contrast, invasive breast cancer showed high levels ofbiomarker expression indicative of cell cycle progression (FIG. 5B).There was a marked increase in the protein expression levels of Ki67,Mcm2, geminin, Aurora A, PLK1 and H3S10ph when comparing normal withaggressive grade 3 tumours (median values: Mcm2 [33.5 v 92.3%, p<0.001],Ki67 [2.8 v 40.2%, p<0.001], geminin [0.98 v 17.4%, p<0.001], Aurora A[0 v 11.7%, p<0.001], PLK1 [0.37 v 14.2%, p<0.001] and H3S10ph [0 v2.5%, p<0.001]). This increase was associated with a marked decrease inthe Mcm2/Ki67 ratio (median values: 9.3 v 1.71%, p<0.001). The reductionin the Mcm2/Ki67 value reflects a switch from a licensednon-proliferating G1 arrested state to an actively proliferating stateand is associated with the expression of S-G2-M markers indicative ofcell cycle progression.

Relationship Between Biomarkers, Tumour DNA Ploidy Status andClinico-Pathological Parameters

The clinico-pathological characteristics of the study are summarised inTable 2. Firstly, we examined the relationship between cell cyclebiomarker expression and the differentiation status of the tumours.Expression levels of all six biomarkers were strongly associated withtumour grade (Table 3), however there is some overlap in thedistribution of biomarker levels between the grades (e.g. Aurora A andPLK1 levels, FIGS. 6A and 6B). These data show an increasing proportionof cells engaged in cycle with increasing tumour anaplasia, but alsoindicate that the biomarkers do not fully distinguish between grades forall patients within each grade. In keeping with these findings, a highlysignificant association between tumour grade and ploidy status was found(p<0.001). The ratios geminin/Ki67, Aurora A/Ki67, Aurora B/Ki67 andH3S10ph/Ki67 showed no significant change with increasing grade,indicating that arrested differentiation was not associated with anaccelerated rate of cell cycle progression in high-grade tumours (Table3). This is in marked contrast with our findings in ovarian cancer inwhich accelerated cell cycle progression was observed with increasingtumour anaplasia (geminin/Ki67: p<0.007, Aurora A/Ki67: p<0.0002,H3S10ph/Ki67: p<0.0002). By contrast, and consistent with our findingsin other tumour types, the Mcm2/Ki67 ratio decreased with increasingtumour grade, reflecting a shift in the proportion of DNA replicationlicensed but non-proliferating cells in well-differentiated tumours toactively cycling cells in poorly-differentiated tumours (Table 3). Thepositive correlation between geminin expression and increasing tumouranaplasia and genomic instability indicates that this origin licensingrepressor does not appear to behave as a tumour suppressor in breastcancer. This has also been observed in other tumour types, for examplein peripheral B-cell lymphomas and ovarian cancer, in which the numberof geminin expressing cells is proportional to the cell proliferationindex.

To investigate the relationship between the biomarkers and genomicinstability, we linked their expression profiles to tumour DNA content(Table 4). There was a highly significant association between expressionlevels of all cell cycle biomarkers including Ki67 (p<0.001), Mcm2(p=0.009), geminin (p<0.001), Aurora A (p<0.001), PLK1 (p=0.002) andH3S10ph (p<0.001) and genomic instability. There was also a significantdecrease in the Mcm2/Ki67 ratio (p=0.004). Taken together, these datashow an increased proportion of actively cycling cells in the aneuploidtumours compared to diploid tumours. Interestingly, again, as in thecase of the differentiation status of these tumours, there was noevidence of accelerated cell cycle progression in aneuploid tumours andcontrasting with our findings in ovarian cancer in which several cellcycle biomarker/Ki67 ratios increased.

No significant association was found between Ki67, Mcm2, geminin, AuroraA, PLK1 expression and lymph node metastasis (Table 5). A weakassociation with H3S10ph expression was observed (p=0.02). There was astrong inverse association with ER (p=0.007) and PR (p=0.005)expression. This contrast with our findings in ovary in which asignificant association was found between Aurora A (p=0.006), H3S10ph(p=0.002), Aurora A/Ki67 (p=0.003), H3S10ph/Ki67 (p=0.005) and tumourstage, reflecting the role of Aurora A dysregulation in early epithelialovarian tumourigenesis and progression to advanced stage disease.Expression levels of Ki67, Mcm2, geminin, Aurora A, PLK1, H3S10ph showeda strong positive correlation, and ER and PR a negative correlation,with increasing NPI score (Table 6). There was also a significantdecrease in the Mcm2/Ki67 ratio, signifying a switch from licensednon-proliferating state to actively proliferating state with increasingNPI score. Cell cycle biomarker expression was not significantlyassociated with Her2 status, but there was strong inverse associationwith PR expression (p<0.001) (Table 7). There was also an associationbetween increasing NPI score and Her2 over-expression and a weakassociation was observed between aneuploidy and increasing NPI score(Table 8). A weak association was also observed between increasing Her2score and aneuploidy (Chi-squared=3.03, p=0.082).

Relationship Between Biomarkers, Tumour DNA Ploidy Status and PatientOutcome Univariate Analysis

The NPI score was a strong predictor of breast cancer recurrence anddeath in this patient cohort with the hazard of recurrence increasingjust under two-fold per unit of NPI score (HR=1.81 [1.47-2.23], p<0.001)and the hazard of dying increasing just over twofold per unit of NPIscore (HR=2.15 [1.61-2.88], p<0.001). Patient age was not a predictivefactor (Table 9) (FIG. 7A). Ki67, Mcm2, geminin, Aurora A, PLK1, andH3S10ph were identified as strong predictors of breast cancer recurrence(HR=2.77 [1.44-5.30], p=0.002; HR=3 [1.56-5.76], p<0.001; HR=3.93[1.98-7.80], p<0.001; HR=3.31 [1.67-6.57], p<0.001; HR=4.48 [2.21-9.09],p<0.001; HR=3.49[1.76-6.92], p<0.001 respectively) (FIGS. 7B and 7C).These associations were also observed for survival, but were not asstrong due to smaller number of events in this cohort (Mcm2: HR=2.32[0.99-5.43], p=0.05; geminin: HR=2.43 [1.04-5.68], p=0.04; Aurora A:HR=2.18 [0.93-5.12], p=0.07; PLK1: HR=3.46 [1.37-8.71], p=0.009;H3S10ph: HR=3.29 [1.31-8.30], p=0.01). A lower hazard of recurrence wasobserved in the diploid group, but this was not significant (HR=0.62[0.33-1.18], p=0.14). There was a significant increasing trend in thehazard of recurrence and death through increasing categories of Her2expression (HR=1.44 [1.13-1.83], p=0.003 and HR=1.40 [1.02-1.94],p=0.04, respectively).

Predictive Value of Biomarkers Over and Above NPI

Multivariate analysis shows that the effects of these cell cyclebiomarkers remain statistically significant and predictive of cancerrecurrence even after adjusting for NPI. Ki67, Mcm2, geminin, Aurora A,PLK1, and H3S10ph were identified as strong independent predictors ofbreast cancer over and above NPI (HR=2.13 [1.08-4.23], p=0.03; HR=2.22[1.12-4.41], p=0.02; HR=2.64 [1.27-5.49], p=0.01; HR=2.82 [1.37-5.80],p=0.005; HR=3.31 [1.57-6.97], p=0.002; HR=2.07 [1.02-4.20], p=0.04respectively) (FIGS. 8 and 9A-9B). Although there was value in using onecell cycle biomarker to predict recurrence, no added value was achievedby including two or more markers. This is partly because there wascorrelation between markers and clinicopathological variables.Interestingly the mitotic kinases, Aurora A and PLK1 were identified asthe most powerful independent predictors of breast cancer recurrence.

Relationship Between Cell Cycle Phenotype, Clinicopathological Variablesand Patient Outcome

We found that the individual cell cycle phase specific biomarkers arepowerful independent prognostic markers in breast cancer. This raisesthe question whether the cell cycle kinetics or cell cycle phenotype ofa tumour might also have an impact on the pathobiology of thisparticular tumour type. We have previously shown in our in-vitro DNAreplication assays that downregulation of the Mcm2-7 licensing factors,constituents of the DNA helicase, is a ubiquitous downstream mechanismby which the proliferative capacity of cells is lowered as cells exitthe cell division cycle into quiescent (G0), differentiated or senescentout of cycle states (Williams and Stoeber, Curr Opin Cell Biol19:672-679, 2007; Blow and Hodgson, Trends Cell Biol 12:72-78, 2002;Stoeber et al., EMBO J 17:7219-7229, 1998; Stoeber et al., J Cell Sci114:2027-2041, 2001; Kingsbury et al., Exp Cell Res 309:56-67, 2005;Barkley et al., Exp Cell Res 313:3789-3799, 2007). To determine the cellcycle phenotype, we selected a cut-point of 30% for Mcm2 proteinexpression to define a group (Mcm2<30%, phenotype I) in which themajority of tumour cells reside in an out-of-cycle state (FIG. 13, FIG.14). This group (phenotype I), 18% of all tumours, had geminin levels ofless than 7%. This is in keeping with our observations in in-vitroassays and self-renewing tissues that geminin is also tightlydownregulated as cells enter quiescent (G0) and differentiatedout-of-cycle states (Williams and Stoeber, 2007 supra; Eward et al., JCell Sci 117:5875-5886, 2004; Kingsbury et al., 2005 supra; Barkley etal., 2007 supra) (FIG. 4, Table 1). In contrast, most cancers had Mcm2expression levels above 30% (Mcm2>30%) in which a majority of tumourcells reside in an in-cycle state (Williams and Stoeber, 2007 supra)(FIG. 13, FIG. 14, Table 15). Fifty-eight percent of these tumours(phenotype III) displayed active cell cycle progression indicated bygeminin levels above 7%, a cut point defined by the labelling index forthe out-of-cycle state (FIG. 14, Table 15). Notably, a large number ofbreast cancers (phenotype II), 24% of all tumours, displayed an in-cyclephenotype (Mcm2>30%) but expressing geminin levels below 7% indicativeof a G1 delayed or arrested state (Williams and Stoeber, 2007 supra;Stoeber et al., 2001 supra; Blow and Hodgson, 2002 supra; Shetty et al.,Br J Cancer 93:1295-1300, 2005; Dudderidge et al., Clin Cancer Res11:25110-2517, 2005; Gonzalez et al., J Pathol 204:121-130, 2004) (FIG.14, Table 15). Importantly, the distribution of the other S-G2-Mbiomarkers between the three groups exactly mirrors that observed forgeminin, further reinforcing segregation into three distinct cell cyclephenotypes (FIG. 14).

Next, we investigated whether the cell cycle phenotype influencesin-vivo behaviour and its association with clinicopathological variablesincluding NPI. Notably, there was no association with age, tumour size,lymph node metastasis, ER/PR or Her-2 receptor status. However a greaterproportion of grade 3 tumours, those exhibiting arresteddifferentiation, displayed the actively cycling phenotype. This cellcycle profile was also associated with a higher NPI score (p<0.001)(Table 15). Univariate and multivariate analysis adjusted for NPI alsodemonstrated that the cell cycle phenotype was a strong predictor ofdisease-free survival. The actively cycling phenotype (phenotype III)showed a much higher hazard of relapse than phenotypes I and II on bothunivariate and multivariate analysis, HR=3.90 (1.81-8.40), p<0.001 andHR=2.71 (1.81-6.23), p=0.019, respectively (FIG. 15). Intriguingly, analmost identical low hazard of relapse was observed between welldifferentiated out-of-cycle tumours and high grade tumours exhibiting aG1 delayed/arrested phenotype (phenotypes I and II) (HR=1.00[0.22-4.46], p=0.99; FIG. 15). Notably, a strong and significantassociation was observed between breast cancer subtype and cell cyclephenotype (p<0.001). The proportion of patients with an actively cyclingphenotype (phenotype III) was significantly higher in both the Her-2(91%, 10/11) (p=0.003) and triple negative subtypes (96%, 25/26)(p<0.001) than in the luminal subtype (49%, 71/145) (FIG. 16). Whereasthe proportion of hormone receptor negative tumours displaying theout-of-cycle phenotype (phenotype I) and the G1 delayed/arrestedphenotype (phenotype II) was only 4% (1/26) and 9% (1/11) respectively,in the luminal subtype the proportion was 51% (74/145), of which 21%(30/145) displayed phenotype I and 30% (44/145) phenotype II (FIG. 16).

Discussion

Analysis of the complex and redundant pathways that control suchprocesses as proliferation, differentiation, apoptosis and DNA damageresponse by global genome wide analysis is proving constrained as aprognostic tool in breast cancer (Dunkler et al. Eur J Cancer,43:745-751, 2007). Here we have focused on the highly evolutionaryconserved cell cycle machinery which lies downstream of complexsignalling pathways that impact on cell cycle progression and thereforecan be regarded as an integration point for information transducedthrough such pathways. We have shown that this novel form ofmultiparameter cell cycle analysis not only provides novel insights intothe cell cycle kinetics of tumours but is of important prognosticsignificance in a range of tumour types including prostate, renal andovarian cancer.

Our analysis of DNA replication licensing factors and mitotic regulatorsfurther characterises the unusual cell cycle state in premenopausalbreast tissue. Although the growth fraction identified by the standardproliferation marker Ki67 is small, a large number of mammary epithelialcells within the TDLU express Mcm2, indicating that a large number ofcells appear to be licensed and therefore “in-cycle”. However, thesecells fail to express markers of cell cycle progression including theS-G2-M markers geminin, Aurora A, PLK1 and the mitotic marker H3S10ph,indicating that these cells reside in a G1 arrested state. This primed,licensed state in non-proliferating breast may be an evolutionaryadaptation allowing for a rapid response to pregnancy, but also thatfailure to down-regulate the DNA replication licensing pathway mightmake transition to uncontrolled cellular proliferation easier toachieve.

Our cell cycle analysis of breast cancer shows that decreasing levels oftumour differentiation and increasing genomic instability, hallmarks ofthe more aggressive tumours, are associated with increased levels ofMcm2, geminin, Aurora A, PLK1 and H3S10ph, indicative of an increasedproportion of cells engaged in cell cycle. However, in contrast toovary, decreasing levels of tumour differentiation and aneuploidy werenot associated with accelerated cell cycle progression. Moreover, noassociation between tumour stage and cell cycle biomarkers was observed,again contrasting with ovary in which there were highly significantassociations between Aurora A, H3S10ph and tumour FIGO stage. Thisimplies that there are fundamental differences in the dysregulation ofthe cell cycle machinery between different tumour types and which may berelated to different cancer genetic backgrounds.

Our analysis of breast cancer has shown that core constituents of theDNA replication licensing pathway (G1-S regulators) and mitoticmachinery (G2-M regulators) are powerful independent prognostic markersin breast cancer and add value over and above the prognostic value ofthe NPI score alone. Intriguingly, the most powerful prognostic markersof recurrence and survival are the mitotic kinases Aurora A and PLK1,both currently a major focus of small molecule inhibitor cancer drugdiscovery programmes. This raises the possibility that multi-parametercell cycle analysis on biopsy tumour samples could be used as apredictive test for small molecules targeting the cell cycle machinery.Importantly, PLK1 and Aurora A expression showed considerable overlapbetween grades and stage indicating that traditionalclinico-pathological parameters are probably inadequate for predictingtherapeutic response. Our data support the concept of co-evolution ofbiomarker and individualised targeted therapy for the cost effectiveintroduction of novel small molecule inhibitors into clinical practice.In addition to mechanism-based therapeutics multiparameter cell cycleanalysis might also be of value in predicting response to conventionalchemotherapeutic agents and ionizing radiation. Non-proliferating cellswhich have withdrawn from cycle have a particular significance tochemotherapy since they are immune to S phase and mitosis-linked agents.Moreover, cell cycle phase determines a tumour cell's relativeradiosensitivity, with cells being more radiosensitive in G2-M phase,less sensitive in G1 and least sensitive during the latter part of Sphase.

Many of the cell cycle markers studied including Ki67, Mcm2, geminin,Aurora A, PLK1 and H3S10ph were associated with breast cancerrecurrence. Importantly, the effects remain statistically significantafter adjusting for NPI and are therefore independent prognosticfactors. However, these critical components of the cell cycle machinerylie at the convergence point of mitogenic signalling pathways downstreamof immediate early and delayed response genes and the E2Ftranscriptional regulatory control system.

In summary, we have shown that core constituents of the cell cyclemachinery, an integration point for upstream growth regulatory pathways,can greatly enhance prognostic assessment in breast cancer and providesadditional information to standard clinico-pathological parameters andintegrated NPI score. Aurora A and

PLK1 appear to be of particular prognostic importance and may thereforehave potential as predictive markers for selective mitotic kinaseinhibitors that are now entering clinical trials.

Example 2 DNA Replication Licensing Factors and Aurora Kinases areLinked to Aneuploidy and Clinical Outcome in Epithelial Ovarian CancerStudy Cohort.

One hundred and forty-three patients diagnosed with EOC between Jan. 1,1999 and Dec. 31, 2004 were identified from the Ovarian CarcinomaDatabase held in the Department of Oncology (University College LondonHospital Gynaecological Cancer Centre, UCL Hospitals, London, UK).Patients were selected on the basis of available histologic material.Histologic specimens had been reviewed by a gynecological oncologypathologist at diagnosis and assessed for histologic subtype and nucleargrade according to WHO criteria. Most patients had been reviewed aftercompleting treatment every 3 to 6 months for 2 years, and annuallythereafter. The following clinical information was obtained directlyfrom patients' hospital notes: date of birth, date of diagnosis,operative findings including amount of residual disease, Federation ofInternational Obstetricians and Gynecologists (FIGO) stage based onfindings at clinical examination and surgical exploration together withcytology results, CA125 values at diagnosis and relapse, performancestatus at start of chemotherapy, date of relapse, date of lastfollow-up, and date and cause of death. Of the 143 patients, 67 (47%)relapsed within the study period. Mean time to relapse among those whorelapsed was 16.9 months (SD, 11.0 months; range, 0-47 months). Meanfollow-up time among those who had not yet relapsed was 33.2 months (SD,18.5 months; range 5-75 months). Thirty-four of the patients (24%) diedwithin the study period and 107 were still alive at the last follow-up.Mean survival time among those who had died was 21.9 months (SD, 15.6months; range 0-60 months). Mean follow-up time among those who had notyet died was 33.3 months (SD, 18.8 months; range, 5-75 months). Twopatients were lost to follow-up. Ethics committee approval was obtainedfrom the joint UCL/UCLH Committees on the Ethics of Human Research.

Antibodies.

Rabbit polyclonal antibody against human geminin was generated asdescribed (Wharton et al. Br J Cancer; 91:262-9, 2004). Ki67 monoclonalantibody (clone MIB-1) was obtained from DAKO, Mcm2 monoclonal antibody(clone 46) was from BD Transduction Laboratories, Aurora A monoclonalantibody NCL-L-AK2 (clone JLM28) was from Novocastra Laboratories,Aurora B polyclonal antibody Ab2254 was from Abcam PLC, and histone H3phosphorylated on serine 10 (H3S10ph) polyclonal antibody was fromUpstate.

Cell Culture and Synchronization.

HeLa S3 cells (European Collection of Animal Cell Cultures 87110901)were cultured and synchronized as described (Stoeber et al. 2001 supra).Cell cycle synchronization was verified by flow cytometry of isolatednuclei as previously described (Krude et al. Cell; 88:109-19, 1997).Preparation of protein extracts and immunoblotting. HeLa S3 cells wereharvested by treatment with trypsin, washed in PBS, and resuspended inlysis buffer [50 mmol/L Tris-Cl (pH 7.5), 150 mmol/L NaCl, 20 mmol/LEDTA, 0.5% NP40] at 2×10⁷ cells/mL. After incubation on ice for 30 min,the lysate was clarified by centrifugation (13,000×g, 15 min, 4° C.).Lysates were separated by 4% to 20% SDS-PAGE (75 μg protein/well) andimmunoblotted as previously described (Stoeber et al. 2001 supra).Blocking, antibody incubations, and washing steps were done using thefollowing conditions: PBS/0.1° A Tween 20/5% milk for Mcm2 and Aurora A,PBS/1° A Tween 20/10% milk for geminin, and PBS/5% milk for Aurora B andH3S10ph.

Immunohistochemistry.

Archival formalin-fixed, paraffin-embedded tissue obtained at initialdiagnosis was available for all patients, and for each specimen, a blockwas chosen that contained a representative sample of invasive tumour.Consecutive serial sections cut from each paraffin-embedded tissue blockwere used for immunohistochemistry. Three-micrometer sections were cutonto Superfrost Plus slides (Vision BioSystems), dewaxed in xylene, andrehydrated through graded alcohol to water. Tissue sections werepressure-cooked in 0.1 mol/L citrate buffer at pH 6.0 for 2 min andimmunostained using the Bond Polymer Define Detection kit and Bond-Xautomated system (Vision BioSystems). Primary antibodies were applied atthe following dilutions: Ki67 (1:100), Mcm2 (1:2,000), geminin (1:600),Aurora A (1:50), Aurora B (1:200), and H3S10ph (1:300). Coverslips wereapplied with Pertex mounting medium (Cell Path Ltd.). Incubation withoutprimary antibody was used as a negative control and colonic epithelialsections as positive controls.

Protein Expression Profile Analysis.

Protein expression analysis was done by determining the labeling indexof the markers in each tumour, as previously described (Shetty et al.2005 supra. Dudderidge et al. 2005 supra). Slides were evaluated atlow-power magnification (x100) to identify regions of tumour with thehighest intensity of staining. From these selected areas, three to fivefields at ×400 magnification were captured with a charged coupled devicecamera and analysis software (SIS). Images were subsequently printed forquantitative analysis, which was undertaken with the observer unaware ofthe clinicopathologic variables. Both positive and negative cells withinthe field were counted and any stromal or inflammatory cells wereexcluded. Criteria for the identification of positive cells weredependent on the biomarkers for Ki67, Mcm2, geminin, Aurora B, andH3S10ph; cells with any degree of nuclear staining were scored positive.For Aurora A, cells with any degree of nuclear or cytoplasmic stainingwere scored positive (Gritsko et al. 2003 supra). A minimum of 500 cellswere counted for each case. The labeling index was calculated using thefollowing formula: labeling index =number of positive cells/total numberof cells×100. Reassessment of 10 randomly selected cases by anindependent assessor showed high levels of agreement.

DNA Image Cytometry.

For each case, one 40-μm section of paraffin embedded tissue obtainedfrom the same block as that assessed by immunohistochemistry was used toprepare nuclei as described (Sudbo et al. 2001 supra. Haroske et al.1997 supra). The Fairfield DNA Ploidy System (Fairfield Imaging, Ltd.)was used for image processing, analysis, and classification aspreviously described (Sudbo et al. 2001 supra). Lymphocytes and plasmacells were included as internal controls and 40-μm sections ofhigh-grade bladder tumour and normal colonic tissue as external controlsfor aneuploid and diploid populations, respectively. Histograms wereclassified according to published criteria (Sudbo et al. 2001 supra.Haroske et al. 1998 supra). Histograms were classified by twoindependent assessors with a high level of agreement without knowledgeof clinicopathologic variables. For statistical analysis, tetraploid andpolyploid tumours were grouped together with aneuploid tumours.

Statistical Analysis.

Spearman's rank correlation coefficient was used to examine associationsbetween biomarkers. Relationships between biomarker expression andtumour grade, stage, and ploidy status were assessed using nonparametricJonckheere-Terpstra and Mann-Whitney U tests as appropriate. Data werethen summarized as the median value and interquartile range of labelingindices observed across the cohort. Analysis of disease-free and overallsurvival data was carried out using Kaplan-Meier plot (using tertilesfor biomarkers), log-rank test, and Cox regression (treating biomarkersas continuous variables unless stated otherwise). For each biomarker,the cohort was divided into tertile groups on the basis of the labelingindex. Within each tertile group, the proportion remaining that waseither disease-free or alive, for disease-free and overall survival,respectively, was calculated using the Kaplan-Meier method. Hazardratios (HR) with 95% confidence intervals (95% CI) for biomarkers werefirst estimated unadjusted, and then adjusted for age, grade and stage.Patients with incomplete data were excluded from the multivariateanalysis. Candidate biomarkers are listed in Supplementary Table S1. Alltests were two-sided and used a significance level of 0.05 and noallowances were made for multiple hypothesis testing. Analysis wascarried out using SPSS 12.0 for Windows (SPSS, Inc.).

Results Validation of Biomarker Multiparameter Analysis and ItsBiological Implications.

The monospecificity of antibodies against Mcm2, geminin, Aurora A,Aurora B, and H3S10ph was confirmed in total cell extracts fromasynchronous HeLa S3 cells by detection of a single protein with amolecular mass consistent with the reported electrophoretic mobility ofthe corresponding human antigen (FIG. 10A). HeLa S3 cells were selectedin the first instance for in vitro studies as this line has wellcharacterized cell cycle phase transit times and establishedsynchronization protocols. Total cell lysates from synchronized cellswere immunoblotted with the characterized antibodies (FIG. 10B). Mcm2levels did not vary significantly during passage through the cell cycle,whereas geminin expression was restricted to S-G2-M. Aurora A levelsincreased during S phase and peaked during mitosis, with degradationoccurring 2 to 4 h after release from mitotic arrest. Similarly, AuroraB levels were negligible during G1 phase, increased gradually during Sphase to reach a peak during G2-M, and decreased after mitosis. Thepresence of H3S10ph was restricted to mitosis, consolidating therationale for its use as a mitotic marker. Identical cellcycle-dependent expression of these biomarkers was observed insynchronized SK-OV 3 ovarian cancer cells (data not shown). Because Ki67is expressed throughout the cell cycle in proliferating cells andgeminin expression is restricted to the S-G2-M phase, we have proposedthat the geminin/Ki67 ratio may be used as an indicator of the relativelength of G1, and therefore, the rate of cell cycle progression. Thedata described above confirm that cell cycle-dependent expression ofAurora A and Aurora B also enables the use of their ratios with Ki67 asindicators of cell cycle progression. Increased geminin expression isalways restricted to the S-G2-M phase, even in highly aggressivetumours. Our in vitro findings therefore also indicate that an increasein the relative ratio between Aurora A or Aurora B and geminin (ratio>1)would be indicative of overexpression of the kinase during the cellcycle. To assess the prognostic significance of our in vitro findingsand their biological implications in EOC, we analysed the expression ofbiomarkers in a series of 143 cases (FIG. 10C). Protein expression wasalso studied in five cases of normal ovarian tissue. Expression of thebiomarkers was extremely low (<4%) in normal ovarian surface epithelium,in keeping with its lowered proliferative capacity (data not shown). Bycontrast, EOC showed high levels of biomarker expression, indicative ofcell cycle re-entry and proliferation.

Next, we examined the correlations between pairs of biomarkers acrossthe tumour series. The expression levels of Aurora A and Aurora B showeda strong positive correlation with those of their substrate H3S10ph[Spearman correlation, 0.57 (95% CI, 0.45-0.67) and 0.52 (95% CI,0.39-0.63), respectively]. The expression levels of Mcm2, geminin, andH3S10ph were strongly positively correlated with Ki67 levels [Spearmancorrelation, 0.73 (95% CI, 0.64-0.8); 0.74 (95% CI, 0.66-0.81); and 0.52(95% CI, 0.39-0.63), respectively], supporting their role asproliferation markers. Notably, the geminin/Ki67 and Aurora A/Ki67ratios were positively, but less strongly, correlated with H3S10ph[Spearman correlation, 0.25 (95% CI, 0.09-0.40) and 0.42 (95% CI,0.27-0.55), respectively], which reflects changes in the relative lengthof G1 as opposed to prolonged S-G2-M transit times that might arisethrough the activation of intra-S or G2-M checkpoint pathways.

This is consistent with a tumour mass only becoming clinicallydetectable after the tumour cell has undergone a major proportion of itspopulation doublings, approximately 30 doublings out of a total of 40.This number of population doublings represents the maximum masscompatible with life, a point in somatic clonal evolution in which mostcell cycle checkpoint mechanisms have been overridden.

Relationship Between Biomarkers, Tumour DNA Ploidy Status, andClinicopathologic Characteristics.

The clinicopathologic characteristics of the study cohort are summarizedin Table 10. To investigate the relationship between the biomarkers andgenomic instability, we linked their expression profiles to tumour DNAcontent. There was a highly significant association between theexpression levels of all of the biomarkers and several biomarker/Ki67ratios and genomic instability (Table 11), reflecting an increasedproportion of cycling cells and accelerated cell cycle progression inaneuploid tumours as compared with diploid tumours.

All six biomarkers were also strongly associated with tumour grade(Table 12); however, there is some overlap in the distributions ofbiomarker levels between grades (e.g., Aurora A levels; FIG. 11). Thesedata confirm an increasing proportion of cycling cells with increasingtumour anaplasia, but also indicate that the biomarkers do not fullydistinguish between grades for all patients within each grade.

In keeping with these findings, a highly significant association betweentumour grade and ploidy status was found (p<0.001). The ratios amonggeminin/Ki67, Aurora A/Ki67, Aurora B/Ki67, and H3S10ph/Ki67 were alsosignificantly associated with tumour differentiation (Table 12),indicative of an accelerated rate of cell cycle progression inhigh-grade tumours. By contrast, and consistent with our findings inother tumour types, the Mcm2/Ki67 ratio decreased with increasing tumourgrade (Table 12), reflecting a shift in the proportion of DNAreplication licensed, but non-proliferating cells in well-differentiatedtumours to actively cycling cells in poorly differentiated tumours. Thepositive correlation between geminin expression and increasing tumouranaplasia and genomic instability (Tables 11 and 12) indicates that thislicensing repressor does not behave as a tumour suppressor in EOC.

A significant association was found between Aurora A, H3S10ph, AuroraA/Ki67, H3S10ph/Ki67 and tumour stage (Table 13). This suggests thatAurora A dysregulation might be a key event in early epithelial ovariantumourigenesis and progression to advanced stage disease. Furthermore,advanced stage disease was significantly associated with an increase inthe Aurora A/geminin ratio (p=0.04; Table 13), also supporting a linkbetween Aurora A dysregulation and tumour progression.

Relationship Between Biomarkers, Tumour DNA Ploidy Status, and PatientOutcome Univariate Analysis

Aurora A (p=0.01; FIG. 12A), Aurora A/Ki67, Aurora B/Ki67, and H3S10ph(Table 14) were all significantly associated with shorter disease-freesurvival but not overall survival. Patient age, tumour grade, and stagewere also predictive of disease-free survival, with younger patients,well-differentiated tumours, and particularly, early stage diseasehaving a significantly longer time-to-relapse [HR, 1.02 (1.00-1.05),p=0.05; HR, 1.59 (1.03-2.45), p=0.04; HR, 2.07 (1.58-2.71), p<0.0001,respectively]. Patient age and tumour stage also predicted overallsurvival [HR, 1.05 (1.02-1.09), p=0.003; HR, 3.21 (1.33-7.79), p=0.01,respectively] but tumour grade did not (p=0.70), emphasizing thelimitations of the current grading systems. Tumour ploidy status alsosignificantly correlated with disease-free survival [HR, 1.80(1.05-3.08), p=0.03; FIG. 12B], with a trend towards shorter overallsurvival in patients with aneuploid tumours, although this did not reachstatistical significance [HR, 1.95 (0.88-4.31), p=0.10].

We subdivided our series into two groups; early stage disease (FIGOstages I and II) and advanced stage disease (FIGO stages III and IV) tomore precisely define the specific subgroups for which the biomarkersmay have particular prognostic importance. Both Aurora A and the AuroraA/Ki67 ratio were strongly predictive of shorter disease-free survival[HR, 1.72 (1.19-2.48), p=0.004 (FIG. 12C); HR, 1.59 (1.13-2.24),p=0.008, respectively] and overall survival [HR, 1.81 (1.14-2.87),p=0.01 (FIG. 12E); HR, 1.68 (1.11-2.54), p=0.01, respectively] in theearly stage subgroup. This association was not found in the advancedstage subgroup [HR, 1.06 (0.81-1.37), p=0.67; HR, 1.04 (0.90-1.20),p=0.58 for disease-free survival; and HR, 0.88 (0.58-1.33), p=0.88; HR,0.89 (0.69-1.15), p=0.36 for overall survival, respectively]. Tumourploidy status also predicted disease-free survival [HR, 4.58(1.04-20.19), p=0.04; FIG. 12D], with a trend towards shorter overallsurvival in patients with aneuploid tumours [HR, 6.34 (0.82-49.18),p=0.08; FIG. 12D] in the early stage subgroup. However, it lost itspredictive value in the advanced stage subgroup [HR, 1.47 (0.81-2.66),p=0.21 and HR, 1.36 (0.55-3.33), p=0.5 for disease-free survival andoverall survival, respectively].

Multivariate Analysis

Cox regression survival analysis showed that tumour stage was the onlysignificant independent predictor of disease-free survival [HR, 2.06(1.49-2.85), p<0.0001]. Patient age and tumour stage were independentpredictors of overall survival, with older patients and advanced stagetumours having shorter overall survival times [HR, 1.05 (1.01-1.09),p=0.007; HR, 3.19 (1.31-7.75), p=0.01, respectively]. Although severalbiomarkers were significant prognostic factors in univariate analysis,none was a significant predictor of disease-free or overall survivalafter adjustment for age, grade, and stage. This is due partly to thehighly significant associations between the biomarkers and tumour gradeand stage, making it difficult to separate their independent effects.

Discussion

This study was undertaken to gain further insight into biologicalmarkers of EOC that may be of prognostic and predictive value and couldlead to a greater understanding of its pathogenesis. Our findings showthat the Mcm2 and geminin replication licensing factors, and the AuroraA and B kinases, together with their substrate H3S10ph, are ofprognostic value in EOC. The association found between tumourdifferentiation and this set of biomarkers has implications for theiruse as proliferation markers with potential for further improvements inthe current grading system. Our multiparameter analysis shows that itcould also be used to provide information about cell cycle progressionin patient tumour samples, data that translate into important prognosticinformation.

These findings are in keeping with analysis of licensing factors inbreast and renal cell cancer. Furthermore, the highly significantassociation found between this set of biomarkers and tumour ploidystatus suggests that dysregulation of the licensing machinery andmitotic kinases is intricately linked to the development of genomicinstability in EOC. Aurora A plays a regulatory role in several keystages of the G2-M transition. Here, we report an intriguing linkbetween aberrant regulation of Aurora A and EOC progression. Our datashow highly significant associations between Aurora A, H3S10ph andtumour FIGO stage, supporting a view that Aurora A dysregulation mightbe an early event in epithelial ovarian carcinogenesis and suggestingthat its dysregulation might play a role in the progression to advanceddisease.

In line with these findings, the Aurora A/geminin ratio is significantlyhigher in advanced stage tumours, which also suggests that Aurora Aoverexpression might play a role in or might be a result of tumourprogression. In vivo, it is likely that such overexpression is regulatedby not only gene amplification but also other mechanisms such astranscriptional activation and suppression of protein degradation. Ourdata suggest that multiparameter analysis of Aurora A and H3S10ph allowsmolecular staging which could be used to complement clinical stagingmethods. FIGO stage is an important prognostic indicator in EOC,however, surgical and radiological staging methods have theirlimitations. Randomized trials have shown that adjuvant chemotherapy isof particular benefit in suboptimally staged patients with stage Idisease. However, in a recent large randomized controlled trial, only34% of patients were optimally staged according to guidelines (Vegote Iet al Curr. Op. Oncol. 2003; 15:452-5). In those patients who wereinadequately staged, these biomarkers might provide supportive evidenceof either true stage I or more advanced disease, assisting a decisionabout the use of adjuvant chemotherapy. The findings of the ICON1/ACTION trials suggested a small overall benefit for adjuvantchemotherapy (Trimbos J B et al J Natl Cancer Inst 2003; 95:105-12), butit remains unclear which adequately staged patients with stage I diseasereally need chemotherapy.

Aurora A, H3S10ph, and genomic instability are also significantpredictors of disease-free survival in this study cohort. Furthersubgroup analysis showed that Aurora A and tumour ploidy status arepredictive of disease-free survival (with Aurora A expression alsopredicting overall survival) in early disease. However, this associationwas reduced when prognostic factors such as age and stage were takeninto account. By contrast, these variables lost their predictive valuein advanced disease [e.g., HR for Aurora A dropped from 1.72 (1.19-2.48)in early stage disease to 1.06 (0.81-1.37) for advanced stage disease],suggesting that other biological factors may take precedence ininfluencing relapse and outcome in these patients. In addition, thecomplexity and heterogeneity of treatment regimens might mask thepredictive value of these biomarkers in advanced stages.

Taken together, our data are supportive of a biological mechanism bywhich Aurora A dysregulation at an early point during tumourigenesismight contribute to genetic instability, resulting in aggressive tumoursand shorter survival in a subgroup of patients with early stage disease.

DNA replication licensing factors and mitotic kinases are criticalregulators of cell cycle progression, and thus, are the focus of currenttherapeutic drug development programs. Here, we have shown thatmultiparameter expression analysis of core regulators of the G1-S andG2-M transitions allows the assessment of the rate of cell cycleprogression in individual patient tumour samples, variables linked tothe biological behavior of these tumours. This type of analysis could beused as a predictive test for small molecules targeting the cell cyclemachinery or upstream growth signal transduction pathways thataccelerate cell cycle progression. Moreover, the observation that AuroraA expression does not fully distinguish between grades shows thattraditional clinicopathologic variables do not always allow theprediction of therapeutic response, supporting the concept ofcoevolution of biomarker and individualized targeted therapy. In view ofthe recent development of specific Aurora kinase inhibitors, our datahave important implications—prognostic, predictive, and therapeutic—forthe use of Aurora A as a biomarker and potential therapeutic target.

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1. A method for determining a treatment protocol for a subject havingcancer, the method comprising the in vitro steps of: a) assessing thelevel of a first biomarker selected from at least one of Mcm2 to 7 in abiological sample from the subject; and b) assessing the level of asecond biomarker selected from at least one of geminin, Aurora A, Plk1and H3S10ph in a biological sample from the subject, wherein thecombination of the level of the first biomarker compared to apre-determined value and the level of the second biomarker compared to apredetermined value is indicative of the treatment regimen prescribedfor the subject.
 2. A method for predicting therapeutic treatmentresponse of a subject having cancer, the method comprising the steps of:a) assessing a level of a first biomarker selected from at least one ofMcm2 to 7 in a biological sample from the subject; and b) assessing thelevel of a second biomarker selected from at least one of geminin,Aurora A, Plk1 and H3S10ph in a biological sample from the subject;wherein the combination of the level of the first biomarker compared toa pre-determined value and the level of the second biomarker compared toa predetermined value is indicative of the efficacy of the therapeutictreatment.
 3. A method for determining the progression of a cancer in asubject, comprising the in vitro steps of: a) assessing the level of afirst biomarker selected from at least one of Mcm2 to 7 in a biologicalsample from the subject; and b) assessing the level of a secondbiomarker selected from at least one of geminin, Aurora A, Plk1 andH3S10ph in a biological sample from the subject, wherein the combinationof the level of the first biomarker compared to a pre-determined valueand the level of the second biomarker compared to a predetermined valueis indicative of cancer progression in the subject.
 4. The method ofclaim 1, further comprising assessing the level of a third biomarkerselected from at least one of geminin, Aurora A, Plk1 and H3S10ph in thebiological sample from said subject, wherein the second and thirdbiomarkers are different.
 5. The method of claim 1, wherein when thelevel of the first biomarker compared to a pre-determined value is lowand the level of the second biomarker compared to a pre-determined valueis low, the treatment regimen is selected from one or more of: a)monitoring; and b) treatment with non-cell-cycle phase specificchemotherapeutic agents.
 6. The method of claim 1, wherein when thelevel of the first biomarker compared to a predetermined value is highand the level of the second biomarker compared to a pre-determined valueis low, the treatment regimen is selected from one or more of: a)monitoring; and b) treatment with G1 or non-cell cycle phase specificchemotherapeutic agents.
 7. The method of claim 1, wherein when thelevel of the first biomarker compared to a pre-determined value is highand the level of the second biomarker compared to a pre-determined valueis high, the treatment regimen is treatment with S, G2 or M cell cyclephase specific chemotherapeutic agents.
 8. The method of claim 1,wherein the biological sample is selected from the group consisting oftumor biopsy tissue, whole blood, blood plasma, blood serum, cervicalsmears, urine, prostatic massage specimens, bronchio-lavage, sputum andbrushings from the alimentary tract.
 9. The method of claim 1, whereinthe level of the first and second biomarker is determined using animmunological assay method.
 10. The method of claim 9, wherein theimmunological assay method is selected from the group consisting ofimmunohistochemistry, immunocytochemistry, dot blot analysis, slot blotanalysis, RIA, peptide microarray, and ELISA.
 11. The method of claim 1,wherein the level of the first and second biomarker is determined usinga molecular biological-based assay methods.
 12. The method of claim 11,wherein the molecular biological-based assay method is selected from thegroup consisting of Northern blot analysis, Southern blot analysis,Western blot analysis, RT-PCR, PCR, nucleic acid sequence basedamplification assays (NASBA), transcription mediated amplification(TMA), or computerized detection matrix.
 13. The method of claim 1,wherein the subject has cancer selected from the group consisting ofbreast cancer, endometrial cancer, ovarian cancer, epithelial ovariancancer, lung cancer, prostate cancer, kidney cancer, bladder cancer,cancer of the oral mucosa, oesophageal cancer, cancer of thelymphreticular system, brain cancer, genito-urinary cancer, skin cancer,colon cancer, stomach cancer, bladder cancer, cancer of the urethra andcancer of the aerodigestive tract.
 14. The method of claim 1, whereinthe first and the second biomarker can be measured sequentially orconcurrently.
 15. The method of claim 1, wherein the level of the firstbiomarker is measured before measuring the level of the secondbiomarker.
 16. The method of claim 2, further comprising assessing thelevel of a third biomarker selected from at least one of geminin, AuroraA, Plk1 and H3S10ph in the biological sample from said subject, whereinthe second and third biomarkers are different.
 17. The method of claim3, further comprising assessing the level of a third biomarker selectedfrom at least one of geminin, Aurora A, Plk1 and H3S10ph in thebiological sample from said subject, wherein the second and thirdbiomarkers are different.
 18. The method of claim 2, wherein the subjecthas cancer selected from the group consisting of breast cancer,endometrial cancer, ovarian cancer, epithelial ovarian cancer, lungcancer, prostate cancer, kidney cancer, bladder cancer, cancer of theoral mucosa, oesophageal cancer, cancer of the lymphreticular system,brain cancer, genito-urinary cancer, skin cancer, colon cancer, stomachcancer, bladder cancer, cancer of the urethra and cancer of theaerodigestive tract.
 19. The method of claim 3, wherein the subject hascancer selected from the group consisting of breast cancer, endometrialcancer, ovarian cancer, epithelial ovarian cancer, lung cancer, prostatecancer, kidney cancer, bladder cancer, cancer of the oral mucosa,oesophageal cancer, cancer of the lymphreticular system, brain cancer,genito-urinary cancer, skin cancer, colon cancer, stomach cancer,bladder cancer, cancer of the urethra and cancer of the aerodigestivetract.